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  • 1. Azar, J.C.
    et al.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    Automated Tracking of the Carotid Artery in Ultrasound Image Sequences Using a Self Organizing Neural Network2010In: Proceedings of 20th International Conference on Pattern Recognition (ICPR 2010), Istanbul, Turkey, Istanbul, Turkey, 2010, p. 2548-2551Conference paper (Refereed)
    Abstract [en]

    An automated method for the segmentation and tracking of moving vessel walls in 2D ultrasound image sequences is introduced. The method was tested on simulated and real ultrasound image sequences of the carotid artery. Tracking was achieved via a self organizing neural network known as Growing Neural Gas. This topology-preserving algorithm assigns a net of nodes connected by edges that distributes itself within the vessel walls and adapts to changes in topology with time. The movement of the nodes was analyzed to uncover the dynamics of the vessel wall. By this way, radial and longitudinal strain and strain rates have been estimated. Finally, wave intensity signals were computed from these measurements. The method proposed improves upon wave intensity wall analysis, WIWA, and opens up a possibility for easy and efficient analysis and diagnosis of vascular disease through noninvasive ultrasonic examination.

  • 2.
    Bergholm, Fredrik
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    Larsolle, A.
    Acquiring instantaneous multispectral imagery using a single image sensor with multiple filter mosaic2007Conference paper (Other academic)
  • 3.
    Hamid Mohammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Karbalaie, Abdolamir
    KTH, School of Technology and Health (STH), Medical Engineering.
    Montazeri, Mohammad Mehdi
    Islamic Azad University, Khomeini Shahr.
    Using Spectral Descriptive Signatures for Industrial Plume Detection2012In: WSEAS Transactions on Environment and Development, ISSN 2224-3496, Vol. 8, no 4, p. 120-132Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel approach for anomaly detection base on computing and utilizing descriptive spectral signatures. The goal of the work is to distinguish between contaminated and normal water areas within a region of investigation. A site-independent approach was developed by considering descriptive spectral signatures characterising normal sweat lake water as reference spectral features. Thereafter, it was possible to detect and determine the distribution of industrial outlet plumes which usually have spectral characteristics that deviate from the surrounding unaffected normal waters. The method was evaluated on airborne hyperspectral remotely-sensed image-data acquired over the region of Norrsundet, Sweden. In this region, areas of different water types were found, such as riverine sweet water, coastal salt seawater, as well as waste water discharged from paper-pulp industries. The work aimed at identifying these types of waters and their distributions. The needed reference descriptive spectral signatures of uncontaminated normal water were generated by using a dataset consisting of laboratory measurements of chlorophyll-a and phaeophytine-a concentrations and the corresponding field reflectance spectra collected at 22 sampling stations in Lake Erken, Sweden. The final results, showing the locations and distributions of contaminated and normal water areas, are in full agreement with field observations in the investigated region.

  • 4.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Activation by Collective Learning, Performing Coursework Activities by Team Work and Obtaining Individual Grades2012Conference paper (Other academic)
  • 5.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Affordable simultaneous hyperspectral imaging2013In: Sensor Review, ISSN 0260-2288, E-ISSN 1758-6828, Vol. 33, no 3, p. 257-266Article in journal (Refereed)
    Abstract [en]

    Purpose - The aim of the research project which resulted in this work is to achieve a cost-effective approach for instantaneous hyperspectral imaging. Design/methodology/approach - This paper presents a simulation study and an experimental evaluation of a novel imaging spectroscopy technique, where multi-channel image data are acquired instantaneously and transformed into spectra by using a statistical modelling approach. A digital colour camera equipped with an additional colour filter array was used to acquire an instantaneous single image that was demosaicked to generate a multi-channel image. A statistical transformation approach was employed to convert this image into a hyperspectral one. Findings - The feasibility of this method was investigated through extensive simulation and experimental tasks where promising results were obtained. Practical implications The small size of the initially acquired single instantaneous image makes this approach useful for applications where video-rate hyperspectral imaging is required. Originality/value - For the first time, a simplified prototype of this novel imaging spectroscopy technique was built and evaluated experimentally. And the results were compared with those of a more ideal simulation study. Recommendations for how to improve the prototype were also suggested as a result of the comparison between the simulation and the prototype evaluation results.

  • 6.
    Hamid Muhammed, Hamed
    Uppsala universitet.
    Characterizing and Estimating Fungal Disease Severity in Wheat2004Conference paper (Other academic)
  • 7.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Computerized Examination (e-exam) with Multiple Choice and Essay Questions2012Conference paper (Other academic)
  • 8.
    Hamid Muhammed, Hamed
    Uppsala Univ, Ctr Image Anal, .
    Hyperspectral crop reflectance data for characterising and estimating fungal disease severity in wheat2005In: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 91, no 1, p. 9-20Article in journal (Refereed)
    Abstract [en]

    Many studies have shown the usefulness of hyperspectral crop reflectance data for detecting plant pathological stress. However, there is still a need to identify unique signatures for specific stresses amidst the constantly changing background associated with normal crop growth and development. Comparing spatial and temporal patterns in crop spectra can provide such signatures. This work was concerned with characterising and estimating fungal disease severity in a spring wheat crop. This goal can be accomplished by using a reference data set consisting of hyperspectral crop reflectance data vectors and the corresponding disease severity field assessments. The hyperspectral vectors were first normalised into zero-mean and unit-variance vectors by performing various combinations of spectral- and band-wise normalisations. Then, after applying the same normalisation procedures to the new hyperspectral data, a nearest-neighbour classifier was used to classify the new data against the reference data. Finally, the corresponding stress signatures were computed using a linear transformation model. High correlation was obtained between the classification results and the corresponding field assessments of fungal disease severity, confirming the usefulness and efficiency of this approach. The effects of increased disease severity could be characterised by analysing the resulting disease signatures obtained when applying the different normalisation procedures. The low computational load of this approach makes it suitable for real-time on-vehicle applications.

  • 9.
    Hamid Muhammed, Hamed
    Uppsala universitet.
    Hyperspectral Image Generation, Processing and Analysis2005Doctoral thesis, monograph (Other academic)
  • 10.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Image Enhancement And Reduction Of Radiation Dose For Panoramic Dental X-Ray Imaging2013In: Swedish Medical Engineering Conference 2013, Medicinteknikdagarna 2013, 2013Conference paper (Other academic)
    Abstract [en]

    1.  Background Reducing the X-ray dose too much produces images with low quality; Noisy, blurred, faded, under exposed. The approach used in this work aims at enhancing image quality by using advanced  automatic image processing algorithms.

    2.  Purpose To minimize X-ray dose exposure during panoramic dental X-ray imaging, in addition to automatically enhancing the acquired X-ray images to achieve high quality images that can be viewed using ordinary monitors.

    3.  Method An automatic, adaptive image enhancement algorithm was developed and implemented on multi-core CPU as well as GPU to achieve real time performance.

    4.  ResultsThe method was tested on panoramic dental X-ray images acquired with varying radiation dose. The results were promising and indicated the possibility of obtaining diagnostically usable images using a reduced dose by 50%. A group of ten dentists and specialists evaluated the resulted images. Figure (1) shows a comparison between an enhanced panoramic dental X-ray acquired with reduced dose by 50% and an original (unprocessed) panoramic dental X-ray acquired with a standard dose.

    5.  Discussion and conclusionsThis study shows the possibility to achieve a number of goals that can lead to better patient safety and better healthcare in general, such as:Minimized X-ray dose to the patient, which can lead to reduced risk of physical damage (e.g. cancer) and psycological consequences (e.g. stress).Better image quality which can lead to better, faster and more accurate and confident diagnostic.The resulted enhanced images can be automatically produced without any noticeable waiting time and viewed using any ordinary monitor (LCD/LED TV or computer screens) without any need for any expensive/exclusive high-dynamic-range displays.

  • 11.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    Image Enhancement Combined with Reduction of X-Ray Dose During PCI-Operations2010Conference paper (Other academic)
  • 12.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    Miniaturized all-reflective holographic Fourier transform imaging spectrometer based on a new all-reflective interferometer2008Patent (Other (popular science, discussion, etc.))
  • 13.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    New approaches for surface water quality estimation in Lake Erken, Sweden, using remotely sensed hyperspectral data2011In: WSEAS Transactions on Environment and Development, ISSN 1790-5079, Vol. 7, no 10, p. 285-314Article in journal (Refereed)
    Abstract [en]

    This work demonstrates the efficiency of using linear statistical modelling for estimation ofconcentrations of various substances in lake water using remotely sensed multi- and hyperspectral imagestogether with extensive field measurements collected over Lake Erken in Sweden. A linear relationship wasassumed between image data and the corresponding field measurements, and the transformation coefficientswere estimated using the least squares method. The resulting coefficients were used to transform new imagedata into the corresponding substance concentrations. Estimation errors were computed and concentration mapswere generated for chlorophyll-a and phaeophytine-a, suspended particulate organic matter SPOM, suspendedparticulate inorganic matter SPIM, as well as total suspended particulate matter SPM (SPOM+SPIM). Goodcorrelation was obtained between estimated and measured values. Backward elimination was performed to findthe most useful spectral bands for the case study of this work. Descriptive spectral signatures, describing theimpact of underlying processes on the spectral characteristics of water, were generated, analysed and also usedto predict the corresponding water quality parameters in image data, with the same estimation accuracy as thelinear statistical model. Feature vector based analysis FVBA was also employed to generate transformationcoefficients that could be used to estimate water quality parameters from image data, also, with the sameaccuracy as the previous methods. Finally, the impact of performing atmospheric correction was investigated,in addition to applying linear statistical modelling for the purpose of combined atmospheric correction andground reflectance estimation.

  • 14.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Optimization of radiation doses in panoramic X-ray examination using automated image processing2014In: IST 2014 - 2014 IEEE International Conference on Imaging Systems and Techniques, Proceedings, 2014, p. 361-364Conference paper (Refereed)
    Abstract [en]

    Radiological techniques based on X-rays are well established in medical diagnostics and there are known risks associated with the use of ionizing radiation like X-rays. That explains why the X-ray technology is constantly under development in the pursuit of new technologies that can contribute to reduce radiation dose to patients. Since the reduction of a radiation dose generally results in a poorer image quality, we have investigated whether the use of digital image processing can provide panoramic radiographs with enhanced image quality. An automated image processing algorithm was proposed and employed for this purpose. Panoramic X-ray examination is an important and common tool in dental radiology, used especially for children and teenagers. The technique is used to create an overview of a patient's jaw.

  • 15.
    Hamid Muhammed, Hamed
    Centre for Image Analysis, Uppsala University.
    Unsupervised Fuzzy Clustering Using Weighted Incremental Neural Networks2004In: International Journal of Neural Systems, ISSN 0129-0657, E-ISSN 1793-6462, Vol. 14, no 6, p. 355-371Article in journal (Refereed)
    Abstract [en]

    A new more efficient variant of a recently developed algorithm for unsupervised fuzzy clustering is introduced. A Weighted Incremental Neural Network (WINN) is introduced and used for this purpose. The new approach is called FC-WINN (Fuzzy Clustering using WINN). The WINN algorithm produces a net of nodes connected by edges, which reflects and preserves the topology of the input data set. Additional weights, which are proportional to the local densities in input space, are associated with the resulting nodes and edges to store useful information about the topological relations in the given input data set. A fuzziness factor, proportional to the connectedness of the net, is introduced in the system. A watershed-like procedure is used to cluster the resulting net. The number of the resulting clusters is determined by this procedure. Only two parameters must be chosen by the user for the FC-WINN algorithm to determine the resolution and the connectedness of the net. Other parameters that must be specified are those which are necessary for the used incremental neural network, which is a modified version of the Growing Neural Gas algorithm (GNG). The FC-WINN algorithm is computationally efficient when compared to other approaches for clustering large high-dimensional data sets.

  • 16.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Using Weighted Fixed Neural Networks for Unsupervised Fuzzy Clustering2002In: International Journal of Neural Systems (IJNS), ISSN 1793-6462, Vol. 12, no 6, p. 425-434Article in journal (Refereed)
    Abstract [en]

    A novel algorithm for unsupervised fuzzy clustering is introduced. The algorithm uses a so-called Weighted Fixed Neural Network (WFNN) to store important and useful information about the topological relations in a given data set. The algorithm produces a weighted connected net, of weighted nodes connected by weighted edges, which reflects and preserves the topology of the input data set. The weights of the nodes and the edges in the resulting net are proportional to the local densities of data samples in input space. The connectedness of the net can be changed, and the higher the connectedness of the net is chosen, the fuzzier the system becomes. The new algorithm is computationally efficient when compared to other existing methods for clustering multi-dimensional data, such as color images.

  • 17.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Azar, J. C.
    Automatic characterization of the physiological condition of the carotid artery in 2D ultrasound image sequences using spatiotemporal and spatiospectral 2D maps2014In: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, Vol. 2014, article id 876267Article in journal (Refereed)
    Abstract [en]

    A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation of wavy patterns along the walls of the carotid artery in a completely automated manner. Spatiotemporal and spatiospectral 2D maps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid artery wall's wavy motion pattern which are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirm the potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system.

  • 18.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Azar, Jimmy C
    Centre for Image Analysis, Uppsala University.
    Semi-Automated Classification of the Physiological Condition of the Carotid Artery in 2D Ultrasound Image Sequences2014In: WSEAS Transactions on Biology and Biomedicine, ISSN 1109-9518, E-ISSN 2224-2902, ISSN E-ISSN 2224-2902, Vol. 11, p. 35-44Article in journal (Refereed)
    Abstract [en]

    Abstract: -A novel automated method for the classification of the physiological condition of the carotid arteryin 2D ultrasound image sequences is introduced. Unsupervised clustering was applied for the segmentationprocess in which both spatial and temporal information was utilized. Radial distension is then measured in theinner surface of the vessel wall, and this characteristic signal is extracted to reveal the detailed radial motion ofthe variable inner part of the vessel wall that is in contact with flowing blood. Characteristic differences in thistime signal were noticed among healthy young, healthy elderly and pathological elderly cases. The discreteFourier transform of the radial distension signal is then computed, and the area subtended by the transform iscalculated and utilized as a diagnostic feature. The method was tested successfully and could differentiateamong the categories of patients mentioned above. Therefore, this computer-aided method would significantlysimplify the task of medical specialists in detecting any defects in the carotid artery and thereby in detectingearly cardiovascular symptoms. The significance of the proposed method is that it is intuitive, semi-automatic,reproducible, and significantly reduces the reliance upon subjective measures.

  • 19.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Bergholm, Fredrik
    KTH, School of Technology and Health (STH), Medical Engineering.
    A system for multi- and hyperspectral imaging2004Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    Arrangement for the production of instantaneous or non-instantaneous multi-band images, to be transformed into multi- or hyperspectral images, comprising light collecting means, an image sensor array, and an instantaneous colour separating means, positioned before the image sensor array, and uniform spectral filters, for restricting imaging to certain parts of the electromagnetic spectrum. A filter unit is positioned before the colour separating means in the optical path in, or close to, converged light. Each filter mosaic consists of a multitude of homogeneous filtering regions. The transmission curves of the filtering regions of a colour or spectral filter mosaic can be partly overlapping, in addition to overlap between these transmission curves and those belonging to the filtering regions of the colour separating means.; The transmission curves of the colour or spectral filter mosaics and the colour separating means are suitably spread out in the intervals of a spectrum to be studied.

  • 20.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Bergholm, Fredrik
    KTH, School of Technology and Health (STH), Medical Engineering.
    Camera-spectrometer for instantaneous multi- and hyperspectral imaging2005Conference paper (Other academic)
  • 21.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Bergholm, Fredrik
    KTH, School of Technology and Health (STH), Medical Engineering.
    Camera-spectrometer for multi- and hyperspectral imaging2005Conference paper (Other academic)
  • 22.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Bergholm, Fredrik
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Sensitivity Analysis of Multichannel Images Intended for Instantaneous Imaging Spectrometry Applications2010In: SIAM Journal on Imaging Sciences, ISSN 1936-4954, E-ISSN 1936-4954, Vol. 3, no 1, p. 79-109Article in journal (Refereed)
    Abstract [en]

    This paper presents a sensitivity analysis of using instantaneous multichannel two-dimensional (2D) imaging to achieve instantaneous 2D imaging spectroscopy. A simulated multiple-filter mosaic was introduced and used to acquire multichannel data which were transformed into spectra. The feasibility of two different transformation approaches (the concrete pseudoinverse approach and a statistical approach) was investigated through extensive experimental tasks. A promising statistical method was identified to be used for accurate estimation of spectra from multichannel data. Comparison between estimated and measured spectra shows that higher estimation accuracy can be achieved when using a larger number of usable multiple-filter combinations in the mosaic.

  • 23.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Darvish, Niloufar
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Öçba, Fatma Nadide
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Bone, Dianna
    Karolinska Hospital, SE-17671 Stockholm, Sweden.
    A New Approach to the Presentation of Myocardial SPECT Images: Radial Slices—Data Reduction without Loss of Information2013In: Engineering, ISSN 1947-394X, Vol. 5, no 10BArticle in journal (Refereed)
    Abstract [en]

    Objective: SPECT data from myocardial perfusion imaging (MPI) are normally displayed as a set of three slices orthogonal to the left ventricular (LV) long axis. For data presentation, the images are orientated about the LV long axis. Therefore, radial slices provide a suitable alternative to standard orthogonal slices, with the advantage of requiring fewer slices to adequately represent the data. In this study, a semi-automatic method is developed for displaying MPI SPECT data as a set of radial slices orientated about the LV axis. The aim is to reduce the number of slices viewed without loss of information and independently from the heart size. Method: Standard short axis slices, orientated perpendicular to the LV axis, are utilized.The skeleton of the segmented myocardium is found and the true LV axis is determined in each central long slice. The LV axis of the whole volume is determined by aligning the axes of all slices. Result: Radial slices centered about this axis were generated by integration over a sector equal to the resolution of the imaging system which was of the order of 1.2 cm. Therefore, assuming a mean LV diameter of 8 cm, 20 slices were sufficient to represent a non-gated study. Gated information could be adequately displayed with 4 slices integrated over an angle of 45. Conclusion: A semi-automatic method for generating radial slices from SPECT MPI short axis slices has been developed.

  • 24.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Kothapalli, Satya V.V.N
    KTH, School of Technology and Health (STH), Medical Engineering.
    Evaluation of Dental Implant Osseointegration Using Ultrasonic Spectrometry: A Phantom Study2014In: WSEAS Transactions on Signal Processing, ISSN 1790-5022, ISSN 2224-3488, Vol. 10, no 1, p. 194-204Article in journal (Refereed)
    Abstract [en]

    One of the challenging and important problems that still needs solution within the field of dental implant surgery is to monitor the osseointegration process. Therefore, this work aims to achieve a reliable noninvasive automatic method to evaluate dental implant stability which is directly related to the grade of osseointegration. For this purpose, an experimental phantom study was performed to simulate this process and evaluate it. Ultrasonic pectrometry was proposed and used to take measurements that were processed and analyzed to estimate the stability of the simulated dental implant. The phantom that was  designed and used in the experiments simulated a jawbone with a dental implant and was made of a little pool filled with soft-tissueequivalent material (with respect to ultrasound waves) and a solid cylinder of fresh oak-wood immersed into it to simulate the jawbone. A metal screw was used to simulate the dental implant. By screwing this screw into or out of the wooden cylinder, varying grades of stiffness and contact between the screw and the wooden tissues were obtained. And by this way, varying screw stability grades which simulate varying osseointegration grades were achieved. Pulse-echo ultrasound was used to measure the power spectra of the received ultrasonic echosignals. These power spectra were, at first, processed and normalized then analyzed by using the partial least squares method to estimate the corresponding implant stability or stiffness grades. The number of screwing turns (for the screw into or out of the wooden cylinder) was used as a measure of stiffness grade.The feasibility of this approach was investigated through experimental tasks and  romising results were achieved. A coefficient of determination R2 of 96.4% and a mean absolute error of ±0.23 screwing turns were achieved when comparing real and estimated  stiffness-grade values, indicating the high efficiency and good accuracy of this approach.

  • 25.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Kothapalli, Satya V.V.N
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Imaging.
    Using Ultrasonic Spectrometry to Estimate the Stability of a Dental Implant Phantom2013In: Engineering, ISSN 1947-3931, E-ISSN 1947-394X, Vol. 5, p. 570-574Article in journal (Refereed)
    Abstract [en]

    A challenging problem in dental implant surgery is to evaluate the stability of the implant. In this simulation study, an experimental phantom is used to represent a jawbone with a dental implant. It is made of a little pool filled with soft-tissue equivalent material and a disc of fresh Oakwood with a metal screw. Varying levels of contact between screw and wood are simulated by screwing in or out the screw. Initially, the screw is screwed in and fixed firmly in wood. Thereafter, the screw is screwed out, a half turn each time, to increase the gap gradually between wood and screw. Pulse-echo ultrasound is used and the power spectra of the received echo-signals are computed. These spectra are normalized then analyzed by using the partial least squares method to estimate the corresponding implant stiffness grade in terms of number of turns when beginning from the initial tight-screw state then screwing out the screw. A coefficient of determination R2 of 96.4% and a mean absolute error of ±0.23 turns are achieved when comparing real and estimated values of stiffness grades, indicating the efficiency of this approach.

  • 26.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Kothapalli, Veeravenkata S
    KTH, School of Technology and Health (STH), Medical Engineering.
    Using Ultrasonic Spectrometry to Estimate the Stability of a Dental Implant Phantom2012Conference paper (Refereed)
  • 27. Hamid Muhammed, Hamed
    et al.
    Larsolle, A.
    Feature vector based analysis of hyperspectral crop reflectance data for discrimination and quantification of fungal disease severity in wheat2003In: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 86, no 2, p. 125-134Article in journal (Refereed)
    Abstract [en]

    The impact of plant pathological stress on crop reflectance can be measured both in broad-band vegetation indices and in narrow or local characteristics of the reflectance spectra. This work is concerned with using the whole spectra in the objective examination of how different parts of the spectrum contribute in describing disease severity in wheat. A hyperspectral reflectance spectrum was considered as a mixed signal, i.e. the integration of the effects of all active objects in the investigated area. Independent component analysis (ICA) was used to blindly separate mixed statistically independent signals. Principal component analysis (PCA) was also used to extract interesting components. The ICA or PCA results had then to be interpreted efficiently. This was achieved by using a technique called feature-vector-based analysis (FVBA), which produces a number of 'component-feature vector' pairs, which represent the spectral signatures and the corresponding weighting coefficients of the different constituting source signals. These weighting coefficients were proportional to field assessments of fungal disease severity in a spring wheat crop, in percentage necrosis of leaf area, and high correlations were shown. Two effects of increased disease severity were observed: (1) a flattening of the green reflectance peak together with a general decrease in reflectance in the near-infrared region and (2) a decrease of the shoulder of the near-infrared reflectance plateau together with a general increase in the visible region between 550 and 750 nm.

  • 28.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Moustafa, Ahmed M. Nasr
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Hassan, Moustapha
    Karolinska University Hospital Huddinge, Stockholm, SWEDEN.
    Skin Cancer Detection Using Temperature Variation Analysis2013In: Engineering, ISSN 1947-394X, Vol. 5, no 10BArticle in journal (Refereed)
    Abstract [en]

    In the medical field, new technologies are incorporated for the sole purpose of enhancing the quality of life for the patients and even for the normal healthy people. Infrared technology is one of the technologies that have some applications in both the medical and biological fields. In this work, the thermal infrared (IR) measurement is used to investigate the potential of skin cancer detection. IR enjoys non-invasive and non-contact advantages as well as favorable cost, apparently. It is also very well developed regarding the technological and methodological aspects. IR per se is an electro-metric radiation that all objects emit when their temperature is above the absolute zero. And the human body is not different in this regard. The IR range extends, ideally, to cover wavelengths from 800 nanometer to few hundred micrometer. Cancer, in modern life, has grown tangibly due to many factors, such as life expectancies increase, personal habits and ultraviolet radiation exposures among others. Moreover, the significant enhancement of technologies has helped identifying more types of cancers than before. The sole purpose of this work is to investigate further IR technology methods and applications not yet matured in skin cancer detection to enhance the detection ability with higher safety level.

  • 29.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Moustafa, A.N.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Hassan, Moustapha
    Department of Laboratory Medicine, Karolinska University Hospital.
    Temperaturvariationsanalys för hudcancerscreening, Poster, Barncancerfondens tredje konferens2013In: Barncancerfondens tredje konferens: Medicinsk Teknik för Barn med Cancer, 2013Conference paper (Other academic)
    Abstract [sv]

    Den här studien visar att det är möjligt att detektera tydliga temperaturskillnader mellan cancervävnad och frisk vävnad. Detta kan vara ett resultat av både angiogenes (processen som leder till nybildning av blodkärl från de minsta befintliga blodkärl) och ökad ämnesomsättning hos cancerceller (medan cancertumörer formas) jämfört med friska normala celler, som ändrar och ökar intensiteten av den termiska IR-strålningen inom cancervävnads områden. Temperaturförändringarna detekterades genom mätningar av termisk IR-strålning inom våglängdsområdet 8-14 μm. Intensiva experiment utfördes på möss med hudcancer. Cancerområdet hade i genomsitt 0.3 – 0.5 °C högre temperatur än de friska grannområdena. Både kvalitativa och kvantitativa statistiska metoder användes för att analysera dessa mätningar. Analysresultaten verifierar användbarheten av att mäta termisk IR-strålning för att kunna detektera hudcancerområden.

  • 30.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Raghavendra, Jammalamadaka
    KTH, School of Technology and Health (STH).
    A New Approach for Rehabilitation and Upper-Limb Prosthesis Control Using Optomyography (OMG)2016In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, p. 27-32Conference paper (Refereed)
    Abstract [en]

    Myoelectric (EMG) and mechano-myographic (MMG) signals recorded during muscular activities are useful not only for monitoring and assessing these activities but can also help in providing effective rehabilitation for disabled patients as well as constructing and controlling sophisticated prosthesis for various amputees. While the existing training methods using EMG and MMG signal data have compelling benefits, many engineering challenges still remain with regard to the sensory control system. Studies show that prosthesis' users support arguments considering the continued development of comfortable, reliable and better functionality of the sensors of the available applications. The aim of this paper is to study muscular activity by using an armband with embedded OptoMyoGraphy (OMG) sensors arranged as a one dimensional sensor array. The armband and the signals' acquisition system are designed and developed at the beginning of the research project. The used sensors are capable of measuring lateral dimensional changes, on the landscape formed by the skin surface, caused due to underlying muscles' activities around the forearm region. As a novel contribution, the paper discusses a possible methodology to control portable upper limb prosthetic devices using the OMG technique. Furthermore, the developed armband can be used as a biofeedback system for rehabilitation purposes in upper-limb amputees (ULAs) cases with below-the-forearm amputation and help them gain control over their remaining sensory-motor system and get rid of phantom and/or residual limb pain (PLP, RLP).

  • 31.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Raghavendra, Jammalamadaka
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Optomyografi (OMG): Ny teknik för muskelaktivitets mätning2015In: Abstract Proceedings of Medicinteknik dagarna 2015, 2015Conference paper (Other academic)
    Abstract [sv]

    Introduktion / Mål

    Den nya tekniken är effektivare och har inte de brister som de existerande teknikerna (elektromyografi EMG och mekanomyografi MMG) lider av, exempelvis, lågt signal till brus förhållande (SNR), interferens med andra biosignaler, interferens med externa signaler från omgivningen, påverkas av hudegenskaperna, komplicerad installation och kalibrering, kan inte användas vid extrema förhållanden, kan inte användas i rymden eller under vatten. Den nya tekniken används av:

    *Idrottare: för att optimera träningen.

    *Patienter och handikappade personer som lider av rörelsestörningar, svaga händer, amputerade händer, rygg eller nackskador.

    *Astronauter: för människa-dator interaktion och robotstyrning.

    Metod

    Den nya tekniken använder fotoelektriska sensorer som mäter reflekterade närainfraröda strålar från hudytan. Den reflekterade signalen varierar då topografiska förändringar, på landskapet som formas av hudytan, sker. Nästan inga bio- eller omgivande signaler interfererar med närainfraröda strålar. Hudens kemiska och fysiska egenskaper påverkar inte heller mätsignalernas kvalitet. Därför registreras signaler av hög SNR. Ytterligare fördelar med den nya tekniken är att den är kostnadseffektiv, mobil, användarvänlig, icke-invasiv och riskfri. Ett armband med två sensorer används för att mäta kontinuerliga tidssignaler när försökspersonen utför ett antal handrörelser.

    Resultat

    Olika handrörelser producerar olika signaler som mäts med hjälp av ett oscilloskop. Varje rörelse ger två signaler eller ett signalpar som skiljer sig från de signalpar som produceras av andra handrörelser.

    Sammanfattning

    Fotoelektriska sensorer används för att mäta reflekterade närainfraröda strålar från huden. Olika muskelaktiviteter och rörelser förändrar topografin av landskapet som formas av hudytan. Miniatyr lysdiod-sensor par byggs in i kläder för att mäta och analysera muskelaktivitet och rörelse. Mätvärdena skickas trådlöst till mobilen för att analyseras och ge återkoppling i realtid för att varna och optimera tränings eller rehabiliterings aktiviteterna.

  • 32.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Raghavendra, Jammalamadaka
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Optomyography (OMG): A Novel Technique for the Detection of Muscle Surface Displacement Using Photoelectric Sensors2015In: Measurements - Proceedings of the 10th International Conference on Bioelectromagnetism, International Society for Bioelectromagnetism, 2015, Vol. 10Conference paper (Refereed)
    Abstract [en]

    Several techniques have been introduced for detecting, measuring, processing and analyzing the signals generated during muscular activities. With the development of more advanced technical solutions, the measurement and analysis of these signals help not only to understand the medical abnormalities and characterization of muscle activities but also to develop human machine interfaces of higher efficiency. In this work, a novel technique to detect and measure the displacement caused on the surface of the skin due to muscle activities was introduced and developed using near-infrared photoelectric sensors. The new technique was coined as OptoMyoGraphy (OMG). In order to evaluate the new technique, real-time pairs of signals were registered using two photoelectric sensors measuring near-infrared rays reflected on the forearm while moving the hand to make a number of different gestures. Different pairs of signals, changing over time and showing repeated patterns while repeating the same hand gesture, were measured for different hand gesture. The signal to noise ratio (SNR) of these signals was good enough to be able to differentiate among the pairs of signals which correspond to different hand gestures using visual inspection.

  • 33.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Zengin, Ziya
    Karadeniz Technical University, Trabzon, Turkey.
    Monte Carlo Simulation and a Review of the Physics of the Positron Annihilation Process in PET2013In: Engineering, ISSN 1947-394X, Vol. 5, no 10BArticle in journal (Refereed)
    Abstract [en]

     In this paper, we investigate the physics of the positron annihilation process, which occurs in a PET imaging system. In particular, the diffusion of beta particles (positrons) within water was addressed. Beta particles are emitted isotropically from the same source point with random directions and randomly chosen energy levels. After traversing a certain distance within water, beta particles lose a certain amount of its energy. The inelastic collisions with atomic electrons are mainly responsible for the energy dissipation of charged particles, such as electrons and positrons (that have low mass). The energy loss rate due to inelastic process is estimated by using the Beta-Bloch formula. These results help in understanding how to develop and implement a computationally efficient Monte Carlo Simulation of the positron annihilation process.

  • 34.
    Karbalaie, Abdolamir
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Erlandsson, Björn-Erik
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Using Homo-Separation of Variables for Solving Systems of Nonlinear Fractional Partial Differential Equations2013In: International journal of mathematics and mathematical sciences, ISSN 0161-1712, E-ISSN 1687-0425, Vol. 2013, p. 8-Article in journal (Refereed)
    Abstract [en]

    A new method proposed and coined by the authors as the homo-separation of variables method is utilized to solve systems oflinear and nonlinear fractional partial differential equations (FPDEs). The new method is a combination of two well-establishedmathematical methods, namely, the homotopy perturbation method (HPM) and the separation of variables method. Whencompared to existing analytical and numerical methods, the method resulting from our approach shows that it is capable ofsimplifying the target problem at hand and reducing the computational load that is required to solve it, considerably.The efficiencyand usefulness of this new general-purposemethod is verified by several examples, where different systems of linear and nonlinearFPDEs are solved.

  • 35.
    Karbalaie, Abdolamir
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Shabani, Maryam
    Sahin Shahr, Isfahan, Iran.
    Mehdi Montazeri, Mohammad
    Khomeini Shahr, Isfahan,Iran.
    Exact Solution of Partial Differential Equation Using Homo-Separation of Variables2014In: International Journal of Nonlinear Science, ISSN 1749-3889, Vol. 17, no 1, p. 84-90Article in journal (Refereed)
    Abstract [en]

    In this study, we find the exact solution of certain partial differential equations (PDE) by proposing and using the Homo-Separation of Variables method. This novel analytical method is a combination of the homotopy perturbation method (HPM) with the separation of variables method. The exact solutions are con-structed by choosing an appropriate initial approximation in addition to only one term of the series obtained by HPM. The proposed method is introduced an efficient tool for solving a wide class of partial differential equations. It is straight-forward, easy to understand and fast requiring low computational load.

  • 36.
    Karbalaie, Abdolamir
    et al.
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Montazeri, M. M.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    New approach to find the exact solution of fractional partial differential equation2012In: WSEAS Transactions on Mathematics, ISSN 1109-2769, E-ISSN 2224-2880, Vol. 11, no 10, p. 908-917Article in journal (Refereed)
    Abstract [en]

    In this study, we present the exact solution of certain fractional partial differential equations (FPDE) by using a modified homotopy perturbation method (MHPM).The exact solutions are constructed by choosing an appropriate initial approximation and only one term of the series obtained by MHPM. The exact solutions for initial value problems of FPDE are analytically derived. The methods introduced an efficient tool for solving a wide class of time-fractional partial differential equations.

  • 37.
    Karbalaie, Abdolamir
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Montazeri, Mohammad M
    Islamic Azad University,Khomeini Shahr, Isfahan, Iran.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Exact Solution of Time-Fractional Partial Differential Equations Using Sumudu Transform2014In: WSEAS Transactions on Mathematics, ISSN 1109-2769, E-ISSN 2224-2880, ISSN E-ISSN 2224-2880, Vol. 13, p. 142-151Article in journal (Refereed)
    Abstract [en]

    Abstract: In this study, we propose a new algorithm to find exact solution of nonlinear time- fractional partialdifferential equations. The new algorithm basically illustrates how two powerful algorithms, the homotopy pertur-bation method and the Sumudu transform method can be combined and used to get exact solutions of fractionalpartial differential equations. We also present four different examples to illustrate the preciseness and effectivenessof this algorithm.

  • 38.
    Khan, Sharifuzzaman
    et al.
    KTH, School of Technology and Health (STH).
    Qidwai, Uvais
    Muhammad, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Qidwai, Umair
    Retinal Image Enhancement Using Laplacian Pyramidal Multi-scaling2014In: IEEE TENSYMP 2014 - 2014 IEEE Region 10 Symposium, 2014, p. 141-146Conference paper (Refereed)
    Abstract [en]

    Early detection of retinal diseases is important to avoid complications and permanent vision loss. In this paper retinal neovascularization and molecular degeneration has been emphasized. Neovascularization is in form of randomly disoriented micro vessels in retina. So image enhancement techniques are excellent way to extract the vessels, find out blood leakages, determine direction of growth and estimate the growth rate with vessel localization. A comparative study has been done on prior retinal image enhancement algorithms. In this project multi-scale image analysis is used as main image enhancement technique with the help of Laplacian Pyramid. The target is achieved by translating an image into several image scales and reconstructing with enhancement tools available in MATLAB image processing toolbox. Results are evaluated with object background contrast ratio, contrast- noise -ratio and 2-D contour plot. The enhanced images appear as a better source for edge detection and vessel extraction compare with the primary image. For this project  normal fundus images from publicly available database are chosen.

  • 39. Larsolle,, A.
    et al.
    Hamid Muhammed, Hamed
    Uppsala universitet.
    Measuring crop status using multivariate analysis of hyperspectral field reflectance with application on disease severity and amount of plant density2005In: Proceedings of 5th European Conference on Precision Agriculture, Uppsala: Sveriges Lantbruksuniversitet, 2005, p. 217-225Conference paper (Other academic)
  • 40.
    Larsolle, A.
    et al.
    SLU, Uppsala.
    Hamid Muhammed, Hamed
    Uppdaga HB, Uppsala, Sweden.
    Measuring crop status using multivariate analysis of hyperspectral field reflectance with application to disease severity and plant density2007In: Precision Agriculture, ISSN 1385-2256, E-ISSN 1573-1618, Vol. 8, no 1-2, p. 37-47Article in journal (Refereed)
    Abstract [en]

    Using spectral reflectance to estimate crop status is a method suitable for developing sensors for site-specific agricultural applications. When developing spectral analysis methods, it is important to know the influence of different crop parameters on the spectral reflectance profile. The objective of this report was to present and evaluate a multivariate method for objective hyperspectral analysis in the examination of how different parts of the reflectance spectrum are affected by disease severity and above ground plant density. Data from two field experiments were used; fungal disease severity assessments in wheat 1998 and above ground plant density measurements 2003. The analysis method consisted of two steps: a preprocessing step where the data was normalized and a classification step for estimating the crop variable. Using only 12% of the data as training data, the method resulted in coefficients of determination (R-2) of 94.3% for the disease severity data and 96.9% for the plant density data. The hyperspectral analysis method presented could also be used to extract spectral signatures of disease severity and plant density using the experimental data. In general, two types of spectral signatures for both data sets, with respect to increasing disease severity and decreasing plant density, were observed (1) a flattening of the green reflectance peak together with a general decrease in reflectance in the near infrared region and, (2) a decrease of the shoulder of the near infrared reflectance plateau together with a general increase in the visible region between 550 and 750 nm.

  • 41.
    Moustafa, Ahmed
    et al.
    KTH, School of Technology and Health (STH).
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Hassan, Moustapha
    Karolinska Institutet.
    Skin Cancer Detection by Temperature Variation Analysis2012Conference paper (Other academic)
  • 42.
    Oliva, Marc Vila
    et al.
    KTH, School of Technology and Health (STH).
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    New Approach for Limited-Angle Problems in Electron Microscope Based on Compressed Sensing2013In: Engineering, ISSN 1947-3931, E-ISSN 1947-394X, Vol. 5, no 10B, p. 575-578Article in journal (Refereed)
    Abstract [en]

    New advances within the recently rediscovered field of Compressed Sensing (CS) have opened for a great variety of new possibilities in the field of image reconstruction and more specifically in medical image reconstruction. In this work, a new approach using a CS-based algorithm is proposed and used in order to solve limited-angle problems (LAPs), like the ones that typically occur in computed tomography or electron microscope. This approach is based on a variant of the Robbins-Monro stochastic approximation procedure, developed by Egaziarian, using regularization by a spatially adaptive filter. This proposal consists on filling the gaps of missing or unobserved data with random noise and enabling a spatially adaptive denoising filter to regularize the data and reveal the underlying topology. This method was tested on different 3D transmission electron microscope datasets that presented different missing data artifacts (e.g, wedge or cone shape). The test results show a great potential for solving LAPs using the proposed technique.

  • 43. Razifar, P.
    et al.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    Engbrant, F.
    Svensson, P. E.
    Olsson, J.
    Bengtsson, E.
    Langstrom, B.
    Bergstrom, M.
    Performance of principal component analysis and independent component analysis with respect to signal extraction from noisy positron emission tomography data - a study on computer simulated images2009In: The Open Neuroimaging Journal, ISSN 1874-4400, E-ISSN 1874-4400, Vol. 3, p. 1-16Article in journal (Refereed)
    Abstract [en]

    Multivariate image analysis tools are used for analyzing dynamic or multidimensional Positron Emission Tomography, PET data with the aim of noise reduction, dimension reduction and signal separation. Principal Component Analysis is one of the most commonly used multivariate image analysis tools, applied on dynamic PET data. Independent Component Analysis is another multivariate image analysis tool used to extract and separate signals. Because of the presence of high and variable noise levels and correlation in the different PET images which may confound the multivariate analysis, it is essential to explore and investigate different types of pre-normalization (transformation) methods that need to be applied, prior to application of these tools. In this study, we explored the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) to extract signals and reduce noise, thereby increasing the Signal to Noise Ratio (SNR) in a dynamic sequence of PET images, where the features of the noise are different compared with some other medical imaging techniques. Applications on computer simulated PET images were explored and compared. Application of PCA generated relatively similar results, with some minor differences, on the images with different noise characteristics. However, clear differences were seen with respect to the type of pre-normalization. ICA on images normalized using two types of normalization methods also seemed to perform relatively well but did not reach the improvement in SNR as PCA. Furthermore ICA seems to have a tendency under some conditions to shift over information from IC1 to other independent components and to be more sensitive to the level of noise. PCA is a more stable technique than ICA and creates better results both qualitatively and quantitatively in the simulated PET images. PCA can extract the signals from the noise rather well and is not sensitive to type of noise, magnitude and correlation, when the input data are correctly handled by a proper pre-normalization. It is important to note that PCA as inherently a method to separate signal information into different components could still generate PC1 images with improved SNR as compared to mean images.

  • 44.
    Yu, Sicong
    et al.
    KTH, School of Technology and Health (STH).
    Hamid Muhammad, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Denoising of SPECT-image sinogram-data before reconstruction2014In: WMSCI 2014 - 18th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings, 2014, Vol. 1, p. 202-206Conference paper (Refereed)
    Abstract [en]

    Nuclear medicine images have low signal-to-noise ratio (SNR) due to several physical limitations which degrade the image quality considerably. In this study, the Gaussian filter and the patch confidence Gaussian filter (PCG) were used to improve the image quality for Single Photon Emission Computed Tomography (SPECT). The new approach applies these filtering methods on the acquired 2D-projections before reconstructing the image. The new approach was evaluated on a SPECT dataset and the performance was compared with several conventional methods presented in the literature.

  • 45.
    Yu, Sicong
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Comparison of Pre- and Post-Reconstruction Denoising Approaches in Positron Emission Tomography2016In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, p. 63-68Conference paper (Refereed)
    Abstract [en]

    In Positron Emission Tomography (PET), image quality is highly degraded by noise. Therefore, two main PETimage denoising approaches can be used: pre- and postreconstruction denoising. In the pre-reconstruction approach the PET sinogram is denoised before forwarding it to the image reconstruction algorithm. On the other hand, the reconstructed PET-image is denoised in the post-reconstruction approach. In this study, comparison of image quality of the resulting images of the pre- and post-reconstruction approaches is performed. In both types of approaches, the Gaussian filter, the Non-Local Means filter (NLM), the Block-Matching and 3D filter (BM3D), the K-Nearest Neighbors Filter (KNN) and the Patch Confidence K-Nearest Neighbors Filter (PCkNN) are utilized. These approaches are evaluated on a simulated PET-phantom dataset, a real-life physical thorax-phantom PET dataset as well as a reallife MicroPET-scan dataset of a mouse. The performance is measured using the Signal-to-Noise Ratio (SNR) in addition to the Contrast-to-Noise Ratio (CNR) in the resulting images.

  • 46.
    Yu, Sicong
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Noise Type Evaluation in Positron Emission Tomography Images2016In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, p. 101-106Conference paper (Refereed)
    Abstract [en]

    In Positron Emission Tomography (PET), the coincident emission of gamma photon pairs constitutes the useful signals that should be detected and processed to reconstruct the desired PET images of the studied objects. However, along with the useful signal, noise is also generated and added to the detected signals that are sorted with respect to their line-ofresponse and arranged as a sinogram for each two-dimensional slice. In this paper, the type and properties of noise in PET sinogram data will be evaluated. Furthermore, the effect of the used linear and non-linear image denoising and reconstruction procedures on the type of noise will be analyzed. For this purpose, the Gaussian filter, the Median filter, the Patch Confidence k-Nearest Neighbor filter (PCkNN) and the Block Matching 3D filter (BM3D) were used to denoise PET image data, as well as the maximum likelihood expectation maximization algorithm (MLEM) and the Filtered Back Projection algorithm (FBP) to reconstruct the PET images.

  • 47.
    Yu, Sicong
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    PET image improvement using the Patch Confidence K-Nearest Neighbors Filter2014Conference paper (Refereed)
    Abstract [en]

    In Positron Emission Tomography (PET), the resulted images are highly deteriorated by noise. In this study, we propose a new denoising framework using the Patch Confidence K-Nearest Neighbors Filter (PCKNN) to reduce noise in the sinogram before forwarding it to the reconstruction procedure. This method has been evaluated on a simulated PET image of a phantom, and the performance has been compared with several conventional methods in the literature. The results have shown that the PET image quality can be substantially improved in term of increased signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR

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