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  • 1.
    Chen, Han
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Xu, Cheng
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Persson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Danielsson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Optimization Of Beam Quality For Photon-Counting Spectral Computed Tomography In Head Imaging: Simulation Study2015In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 2, no 4, p. 043504-1-043504-16, article id 043504Article in journal (Refereed)
    Abstract [en]

    Head computed tomography (CT) plays an important role in the comprehensive evaluation of acutestroke. Photon-counting spectral detectors, as promising candidates for use in the next generation of x-ray CTsystems, allow for assigning more weight to low-energy x-rays that generally contain more contrast information.Most importantly, the spectral information can be utilized to decompose the original set of energy-selectiveimages into several basis function images that are inherently free of beam-hardening artifacts, a potential ad-vantage for further improving the diagnosis accuracy. We are developing a photon-counting spectral detector forCT applications. The purpose of this work is to determine the optimal beam quality for material decomposition intwo head imaging cases: nonenhanced imaging and K-edge imaging. A cylindrical brain tissue of 16-cm diam-eter, coated by a 6-mm-thick bone layer and 2-mm-thick skin layer, was used as a head phantom. The imagingtarget was a 5-mm-thick blood vessel centered in the head phantom. In K-edge imaging, two contrast agents,iodine and gadolinium, with the same concentration (5mg∕mL) were studied. Three parameters that affect beamquality were evaluated: kVp settings (50 to 130 kVp), filter materials (Z¼13to 83), and filter thicknesses [0 to 2half-value layer (HVL)]. The image qualities resulting from the varying x-ray beams were compared in terms oftwo figures of merit (FOMs): squared signal-difference-to-noise ratio normalized by brain dose (SDNR2∕BD) andthat normalized by skin dose (SDNR2∕SD). For nonenhanced imaging, the results show that the use of the 120-kVp spectrum filtered by 2 HVL copper (Z¼29) provides the best performance in both FOMs. When iodine isused in K-edge imaging, the optimal filter is 2 HVL iodine (Z¼53) and the optimal kVps are 60 kVp in terms ofSDNR2∕BD and 75 kVp in terms of SDNR2∕SD. A tradeoff of 65 kVp was proposed to lower the potential riskof skin injuries if a relatively long exposure time is necessarily performed in the iodinated imaging. In the case ofgadolinium imaging, both SD and BD can be minimized at 120 kVp filtered with 2 HVL thulium (Z¼69). Theresults also indicate that with the same concentration and their respective optimal spectrum, the values ofSDNR2∕BD and SDNR2∕SD in gadolinium imaging are, respectively, around 3 and 10 times larger thanthose in iodine imaging. However, since gadolinium is used in much lower concentrations than iodine in theclinic, iodine may be a preferable candidate for K-edge imaging.

  • 2.
    da Silva, Joakim
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Grönberg, Fredrik
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging. Prismatic Sensors AB, Stockholm, Sweden.
    Cederström, Björn
    Persson, Mats
    Sjölin, Martin
    Alagic, Zlatan
    Bujila, Robert
    KTH, School of Engineering Sciences (SCI), Physics. Karolinska University Hospital, Medical Radiation Physics and Nuclear Medicine, Stockholm, Sweden.
    Danielsson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging. Prismatic Sensors AB, Stockholm, Sweden.
    Resolution characterization of a silicon-based, photon-counting computed tomography prototype capable of patient scanning2019In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 6, no 4, article id 043502Article in journal (Refereed)
    Abstract [en]

    Photon-counting detectors are expected to bring a range of improvements to patient imaging with x-ray computed tomography (CT). One is higher spatial resolution. We demonstrate the resolution obtained using a commercial CT scanner where the original energy-integrating detector has been replaced by a single-slice, silicon-based, photon-counting detector. This prototype constitutes the first full-field-of-view silicon-based CT scanner capable of patient scanning. First, the pixel response function and focal spot profile are measured and, combining the two, the system modulation transfer function is calculated. Second, the prototype is used to scan a resolution phantom and a skull phantom. The resolution images are compared to images from a state-of-the-art CT scanner. The comparison shows that for the prototype 19 lp∕cm are detectable with the same clarity as 14 lp∕cm on the reference scanner at equal dose and reconstruction grid, with more line pairs visible with increasing dose and decreasing image pixel size. The high spatial resolution remains evident in the anatomy of the skull phantom and is comparable to that of other photon-counting CT prototypes present in the literature. We conclude that the deep silicon-based detector used in our study could provide improved spatial resolution in patient imaging without increasing the x-ray dose.

  • 3. Lidayova, Kristina
    et al.
    Frimmel, Hans
    Bengtsson, Ewert
    Smedby, Örjan
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization.
    Improved centerline tree detection of diseased peripheral arteries with a cascading algorithm for vascular segmentation2017In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 4, no 2, article id 024004Article in journal (Refereed)
    Abstract [en]

    Vascular segmentation plays an important role in the assessment of peripheral arterial disease. The segmentation is very challenging especially for arteries with severe stenosis or complete occlusion. We present a cascading algorithm for vascular centerline tree detection specializing in detecting centerlines in diseased peripheral arteries. It takes a three-dimensional computed tomography angiography (CTA) volume and returns a vascular centerline tree, which can be used for accelerating and facilitating the vascular segmentation. The algorithm consists of four levels, two of which detect healthy arteries of varying sizes and two that specialize in different types of vascular pathology: severe calcification and occlusion. We perform four main steps at each level: appropriate parameters for each level are selected automatically, a set of centrally located voxels is detected, these voxels are connected together based on the connection criteria, and the resulting centerline tree is corrected from spurious branches. The proposed method was tested on 25 CTA scans of the lower limbs, achieving an average overlap rate of 89% and an average detection rate of 82%. The average execution time using four CPU cores was 70 s, and the technique was successful also in detecting very distal artery branches, e. g., in the foot.

  • 4.
    Liu, Xuejin
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Persson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Bornefalk, Hans
    KTH, School of Engineering Sciences (SCI), Physics.
    Karlsson, Staffan
    KTH, School of Engineering Sciences (SCI), Physics.
    Xu, Cheng
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Danielsson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Huber, Ben
    KTH, School of Engineering Sciences (SCI), Physics.
    Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications2015In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 2, no 3, article id 033502Article in journal (Refereed)
    Abstract [en]

    Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy.

  • 5.
    Liu, Xuejin
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Persson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Bornefalk, Hans
    KTH, School of Engineering Sciences (SCI), Physics.
    Karlsson, Staffan
    KTH, School of Engineering Sciences (SCI), Physics.
    Xu, Cheng
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Danielsson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Huber, Ben
    KTH, School of Engineering Sciences (SCI), Physics.
    Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications (vol 2, 033502, 2015)2016In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 3, no 4, article id 049801Article in journal (Refereed)
  • 6. Marreiros, Filipe M. M.
    et al.
    Rossitti, Sandro
    Karlsson, Per M.
    Wang, Chunliang
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization.
    Gustafsson, Torbjorn
    Carleberg, Per
    Smedby, Örjan
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization.
    Superficial vessel reconstruction with a multiview camera system2016In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 3, no 1, article id 015001Article in journal (Refereed)
    Abstract [en]

    We aim at reconstructing superficial vessels of the brain. Ultimately, they will serve to guide the deformation methods to compensate for the brain shift. A pipeline for three-dimensional (3-D) vessel reconstruction using three mono-complementary metal-oxide semiconductor cameras has been developed. Vessel centerlines are manually selected in the images. Using the properties of the Hessian matrix, the centerline points are assigned direction information. For correspondence matching, a combination of methods was used. The process starts with epipolar and spatial coherence constraints (geometrical constraints), followed by relaxation labeling and an iterative filtering where the 3-D points are compared to surfaces obtained using the thin-plate spline with decreasing relaxation parameter. Finally, the points are shifted to their local centroid position. Evaluation in virtual, phantom, and experimental images, including intraoperative data from patient experiments, shows that, with appropriate camera positions, the error estimates (root-mean square error and mean error) are similar to 1 mm.

  • 7. Marreiros, Filipe M. M.
    et al.
    Rossitti, Sandro
    Karlsson, Per M.
    Wang, Chunliang
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization.
    Gustafsson, Torbjorn
    Carleberg, Per
    Smedby, Örjan
    KTH, School of Technology and Health (STH), Medical Engineering, Medical Image Processing and Visualization.
    Superficial vessel reconstruction with a Multiview camera system (vol 3, 015001, 2016)2016In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 3, no 1, article id 019801Article in journal (Refereed)
  • 8.
    Nordenfur, Tim
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging. Karolinska Institute, Sweden.
    Babic, A.
    Bulatovic, I.
    Giesecke, A.
    Günyeli, E.
    Ripsweden, J.
    Samset, E.
    Winter, R.
    Larsson, Matilda
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging.
    Method comparison for cardiac image registration of coronary computed tomography angiography and 3-D echocardiography2018In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 5, no 1, article id 014001Article in journal (Refereed)
    Abstract [en]

    Treatment decision for coronary artery disease (CAD) is based on both morphological and functional information. Image fusion of coronary computed tomography angiography (CCTA) and three-dimensional echocardiography (3DE) could combine morphology and function into a single image to facilitate diagnosis. Three semiautomatic feature-based methods for CCTA/3DE registration were implemented and applied on CAD patients. Methods were verified and compared using landmarks manually identified by a cardiologist. All methods were found feasible for CCTA/3DE fusion.

  • 9. Pavoni, Marco
    et al.
    Chang, Yongjun
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Park, Sang-Ho
    Smedby, Örjan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging.
    Convolutional neural network-based image enhancement for x-ray percutaneous coronary intervention2018In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 5, no 2, article id 024006Article in journal (Refereed)
    Abstract [en]

    Percutaneous coronary intervention (PCI) uses x-ray images, which may give high radiation dose and high concentrations of contrast media, leading to the risk of radiation-induced injury and nephropathy. These drawbacks can be reduced by using lower doses of x-rays and contrast media, with the disadvantage of noisier PCI images with less contrast. Vessel-edge-preserving convolutional neural networks (CNN) were designed to denoise simulated low x-ray dose PCI images, created by adding artificial noise to high-dose images. Objective functions of the designed CNNs have been optimized to achieve an edge-preserving effect of vessel walls, and the results of the proposed objective functions were evaluated qualitatively and quantitatively. Finally, the proposed CNN-based method was compared with two state-of-the-art denoising methods: K-SVD and block-matching and 3D filtering. The results showed promising performance of the proposed CNN-based method for PCI image enhancement with interesting capabilities of CNNs for real-time denoising and contrast enhancement tasks.

  • 10.
    Persson, Mats
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging. Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA..
    Holmin, Staffan
    Karolinska Inst, Dept Clin Neurosci, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Neuroradiol, Stockholm, Sweden..
    Karlsson, Staffan
    Bornefalk, Hans
    KTH, School of Engineering Sciences (SCI), Physics.
    Danielsson, Mats
    KTH, School of Engineering Sciences (SCI), Physics, Physics of Medical Imaging.
    Subpixel x-ray imaging with an energy-resolving detector2018In: Journal of Medical Imaging, ISSN 2329-4302, E-ISSN 2329-4310, Vol. 5, no 1, article id 013507Article in journal (Refereed)
    Abstract [en]

    The detector pixel size can be a severe limitation in x-ray imaging of fine details in the human body. We demonstrate a method of using spectral x-ray measurements to image the spatial distribution of the linear attenuation coefficient on a length scale smaller than one pixel, based on the fact that interfaces parallel to the x-ray beam have a unique spectral response, which distinguishes them from homogeneous materials. We evaluate the method in a simulation study by simulating projection imaging of the border of an iodine insert with 200 mg/ml I in a soft tissue phantom. The results show that the projected iodine profile can be recovered with an RMS resolution of 5% to 34% of the pixel size, using an ideal energy-resolving detector. We also validate this method in an experimental study by imaging an iodine insert in a polyethylene phantom using a photon-counting silicon-strip detector. The results show that abrupt and gradual transitions can be distinguished based on the transmitted x-ray spectrum, in good agreement with simulations. The demonstrated method may potentially be used for improving visualization of blood vessel boundaries, e.g., in acute stroke care.

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