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Hamid Muhammed, HamedORCID iD iconorcid.org/0000-0002-1831-9285
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Publications (10 of 49) Show all publications
Chen, F., Chen, P., Muhammed, H. H. & Zhang, J. (2017). Intravoxel Incoherent Motion Diffusion for Identification of Breast Malignant and Benign Tumors Using Chemometrics. BioMed Research International, Article ID 3845409.
Open this publication in new window or tab >>Intravoxel Incoherent Motion Diffusion for Identification of Breast Malignant and Benign Tumors Using Chemometrics
2017 (English)In: BioMed Research International, ISSN 2314-6133, E-ISSN 2314-6141, article id 3845409Article in journal (Refereed) Published
Abstract [en]

Theaim of the paper is to identify the breast malignant and benign lesions using the features of apparent diffusion coefficient (ADC), perfusion fraction f, pseudodiffusion coefficient D*, and true diffusion coefficient D from intravoxel incoherent motion (IVIM). There are 69 malignant cases (including 9 early malignant cases) and 35 benign breast cases who underwent diffusion-weighted MRI at 3.0 T with 8 b-values (0 similar to 1000 s/mm(2)). ADC and IVIM parameters were determined in lesions. The early malignant cases are used as advanced malignant and benign tumors, respectively, so as to assess the effectiveness on the result. A predictive model was constructed using Support VectorMachine Binary Classification (SVMBC, also known Support VectorMachine Discriminant Analysis (SVMDA)) and Partial Least Squares Discriminant Analysis (PLSDA) and compared the difference between them both. The.. value and ADC provide accurate identification of malignant lesions with.. = 300, if early malignant tumor was considered as advanced malignant (cancer). The classification accuracy is 93.5% for cross-validation using SVMBC with ADC and tissue diffusivity only. The sensitivity and specificity are 100% and 87.0%, respectively, r(2) (cv) = 0.8163, and root mean square error of cross-validation (RMSECV) is 0.043. ADC and IVIM provide quantitative measurement of tissue diffusivity for cellularity and are helpful with the method of SVMBC, getting comprehensive and complementary information for differentiation between benign and malignant breast lesions.

Place, publisher, year, edition, pages
Hindawi Limited, 2017
National Category
Medical Engineering
Identifiers
urn:nbn:se:kth:diva-209081 (URN)10.1155/2017/3845409 (DOI)000402163200001 ()28630864 (PubMedID)2-s2.0-85021632337 (Scopus ID)
Note

QC 20170619

Available from: 2017-06-19 Created: 2017-06-19 Last updated: 2024-03-18Bibliographically approved
Chen, F., Chen, P.-L. -., Xie, Y.-P. -., Ying, N.-J. -., Hamid Muhammed, H. & Yang, Y. (2017). Rapid Detection for Toxic Capsules with Chromium Based on Hyperspectral Imaging Technology. Jiliang Xuebao/Acta Metrologica Sinica, 38(6), 765-769
Open this publication in new window or tab >>Rapid Detection for Toxic Capsules with Chromium Based on Hyperspectral Imaging Technology
Show others...
2017 (English)In: Jiliang Xuebao/Acta Metrologica Sinica, ISSN 1000-1158, Vol. 38, no 6, p. 765-769Article in journal (Refereed) Published
Abstract [en]

The rapid detection method of chromium content in medicinal capsules based on hyperspectral imaging was studied. Firstly, analysis of medical empty hard gelatin capsule was used as the control group by traditional atomic absorption spectroscopy. Then, the hyperspectral data of 1048 samples were analyzed by dimensionality reduction and qualitative analysis. Finally, the partial least squares discriminant analysis method was used to process the spectral data. If 4 LV are as input features in the partial lease squares discrimination analysis model, the classification accuracy reached 100%, the correlation coefficient of cross validation and sample prediction are 0.923 and 0.972, respectively. Sensitivity and specificity are both 100%. 

Place, publisher, year, edition, pages
Chinese Society for Measurement, 2017
Keywords
Capsule detection, Chromium, Hyperspectral imaging, Metrology, PLS-DA model, Spectral analysis
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:kth:diva-246579 (URN)10.3969/j.issn.1000-1158.2017.06.24 (DOI)2-s2.0-85055623906 (Scopus ID)
Note

QC 20190613

Available from: 2019-06-13 Created: 2019-06-13 Last updated: 2022-12-12Bibliographically approved
Hamid Muhammed, H. & Raghavendra, J. (2016). A New Approach for Rehabilitation and Upper-Limb Prosthesis Control Using Optomyography (OMG). In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016): . Paper presented at THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016) (pp. 27-32). IEEE
Open this publication in new window or tab >>A New Approach for Rehabilitation and Upper-Limb Prosthesis Control Using Optomyography (OMG)
2016 (English)In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, p. 27-32Conference paper, Published 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).

Place, publisher, year, edition, pages
IEEE, 2016
National Category
Medical Materials
Identifiers
urn:nbn:se:kth:diva-198262 (URN)10.1109/IBIOMED.2016.7869814 (DOI)000405596400005 ()2-s2.0-85017514237 (Scopus ID)978-1-5090-4142-8 (ISBN)
Conference
THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016)
Note

QC 20161220

Available from: 2016-12-13 Created: 2016-12-13 Last updated: 2024-03-18Bibliographically approved
Yu, S. & Hamid Muhammed, H. (2016). Comparison of Pre- and Post-Reconstruction Denoising Approaches in Positron Emission Tomography. In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016): . Paper presented at THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016) (pp. 63-68). IEEE
Open this publication in new window or tab >>Comparison of Pre- and Post-Reconstruction Denoising Approaches in Positron Emission Tomography
2016 (English)In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, p. 63-68Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
BM3D, CNR, FB, Image, Denoising, kNN, MLEM, NLM, PCkNN, PET, Positron Emission Tomography, Sinogram Denoising, SNR
National Category
Medical Image Processing
Identifiers
urn:nbn:se:kth:diva-198190 (URN)10.1109/IBIOMED.2016.7869821 (DOI)000405596400012 ()2-s2.0-85017515445 (Scopus ID)978-1-5090-4142-8 (ISBN)
Conference
THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016)
Note

QCR 20161214

QC 20170601

Available from: 2016-12-13 Created: 2016-12-13 Last updated: 2024-03-18Bibliographically approved
Yu, S. & Hamid Muhammed, H. (2016). Noise Type Evaluation in Positron Emission Tomography Images. In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016): . Paper presented at THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016) (pp. 101-106). IEEE
Open this publication in new window or tab >>Noise Type Evaluation in Positron Emission Tomography Images
2016 (English)In: THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016), IEEE, 2016, p. 101-106Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
Denoising, Image, Reconstruction, Noise, Type, PET, Poisson, Noise, Positron, Emission, Tomography, Sinogram
National Category
Medical Image Processing
Identifiers
urn:nbn:se:kth:diva-198195 (URN)10.1109/IBIOMED.2016.7869828 (DOI)000405596400019 ()2-s2.0-85017515201 (Scopus ID)978-1-5090-4142-8 (ISBN)
Conference
THE 1ST 2016 INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED 2016)
Note

QC 20161214

Available from: 2016-12-13 Created: 2016-12-13 Last updated: 2024-03-18Bibliographically approved
Hamid Muhammed, H. & Raghavendra, J. (2015). Optomyografi (OMG): Ny teknik för muskelaktivitets mätning. In: Abstract Proceedings of Medicinteknik dagarna 2015: . Paper presented at Medicinteknik dagarna 2015, Uppsala.
Open this publication in new window or tab >>Optomyografi (OMG): Ny teknik för muskelaktivitets mätning
2015 (Swedish)In: Abstract Proceedings of Medicinteknik dagarna 2015, 2015Conference paper, Oral presentation with published abstract (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.

Keywords
Optomyografi, OMG, muskelaktivitets mätning
National Category
Medical Equipment Engineering Medical Laboratory and Measurements Technologies
Research subject
Medical Technology
Identifiers
urn:nbn:se:kth:diva-179725 (URN)
Conference
Medicinteknik dagarna 2015, Uppsala
Note

QC 20160121

Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2022-06-23Bibliographically approved
Hamid Muhammed, H. & Raghavendra, J. (2015). Optomyography (OMG): A Novel Technique for the Detection of Muscle Surface Displacement Using Photoelectric Sensors. In: Measurements - Proceedings of the 10th International Conference on Bioelectromagnetism: . Paper presented at 10th International Conference on Bioelectromagnetism, ISBEM 2015. International Society for Bioelectromagnetism, 10
Open this publication in new window or tab >>Optomyography (OMG): A Novel Technique for the Detection of Muscle Surface Displacement Using Photoelectric Sensors
2015 (English)In: Measurements - Proceedings of the 10th International Conference on Bioelectromagnetism, International Society for Bioelectromagnetism, 2015, Vol. 10Conference paper, Published 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.

Place, publisher, year, edition, pages
International Society for Bioelectromagnetism: , 2015
Keywords
OptoMyoGraphy; OMG; moving-hand gesture; photoelectric sensor; near infrared; NIR; muscle surface displacement, Optomyografi, muskelaktivitets mätning
National Category
Medical Laboratory and Measurements Technologies Medical Equipment Engineering
Research subject
Medical Technology
Identifiers
urn:nbn:se:kth:diva-179722 (URN)
Conference
10th International Conference on Bioelectromagnetism, ISBEM 2015
Projects
OptoMyoGraphy / Optomyografi (OMG)
Note

QC 20160121

Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2022-06-23Bibliographically approved
Hamid Muhammed, H. & Azar, J. C. (2014). Automatic characterization of the physiological condition of the carotid artery in 2D ultrasound image sequences using spatiotemporal and spatiospectral 2D maps. International Journal of Biomedical Imaging, 2014, Article ID 876267.
Open this publication in new window or tab >>Automatic characterization of the physiological condition of the carotid artery in 2D ultrasound image sequences using spatiotemporal and spatiospectral 2D maps
2014 (English)In: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, Vol. 2014, article id 876267Article in journal (Refereed) Published
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.

Keywords
Cardiovascular system, Automatic differentiations, Automatic feature extraction, Frequency domains, Physiological condition, Physiological properties, Spectral characteristics, Temporal propagation, Visual inspection
National Category
Other Medical Sciences
Identifiers
urn:nbn:se:kth:diva-161801 (URN)10.1155/2014/876267 (DOI)000215623000020 ()24971088 (PubMedID)2-s2.0-84902142221 (Scopus ID)
Note

QC 20150317

Available from: 2015-03-17 Created: 2015-03-17 Last updated: 2022-06-23Bibliographically approved
Yu, S. & Hamid Muhammad, H. (2014). Denoising of SPECT-image sinogram-data before reconstruction. In: WMSCI 2014 - 18th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings: . Paper presented at 18th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2014, 15 July 2014 through 18 July 2014 (pp. 202-206). , 1
Open this publication in new window or tab >>Denoising of SPECT-image sinogram-data before reconstruction
2014 (English)In: WMSCI 2014 - 18th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings, 2014, Vol. 1, p. 202-206Conference paper, Published 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.

Keywords
2D Projections, Low SNR, Patch Confidence Gaussian Filter PCG, PCKNN, Sinogram, SPECT, Cybernetics, Gaussian distribution, Image quality, Information science, Nuclear medicine, Particle beams, Single photon emission computed tomography, Gaussian filters, Sinograms, Signal to noise ratio
National Category
Radiology, Nuclear Medicine and Medical Imaging Physical Sciences
Identifiers
urn:nbn:se:kth:diva-167583 (URN)2-s2.0-84923135770 (Scopus ID)9781941763049 (ISBN)
Conference
18th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2014, 15 July 2014 through 18 July 2014
Note

QC 20150601

Available from: 2015-06-01 Created: 2015-05-22 Last updated: 2022-06-23Bibliographically approved
Hamid Muhammed, H. & Kothapalli, S. V. .. (2014). Evaluation of Dental Implant Osseointegration Using Ultrasonic Spectrometry: A Phantom Study. WSEAS Transactions on Signal Processing, 10(1), 194-204
Open this publication in new window or tab >>Evaluation of Dental Implant Osseointegration Using Ultrasonic Spectrometry: A Phantom Study
2014 (English)In: WSEAS Transactions on Signal Processing, ISSN 1790-5052, Vol. 10, no 1, p. 194-204Article in journal (Refereed) Published
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.

Keywords
Contact grade, Partial least squares PLS, Power spectra, Pulse-Echo ultrasound, Screw dental implant stability, Spectral analysis, Spectroscopy, Stiffness grade
National Category
Medical Engineering
Identifiers
urn:nbn:se:kth:diva-154341 (URN)2-s2.0-84896986212 (Scopus ID)
Note

QC 20150414

Available from: 2014-10-17 Created: 2014-10-17 Last updated: 2022-06-23Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1831-9285

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