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IEEE Transactions on Medical Imaging

Mohammad Honarvar, Ramin Sahebjavaher, Robert Rohling, Septimiu Salcudean
In quantitative elastography, maps of the mechanical properties of soft tissue, or elastograms, are calculated from the measured displacement data by solving an inverse problem. The model assumptions have a significant effect on elastograms. Motivated by the high sensitivity of imaging results to the model assumptions for in-vivo Magnetic Resonance Elastography (MRE) of the prostate, we compared elastograms obtained with four different methods. Two FEM-based methods developed by our group were compared with two other commonly used methods, Local Frequency Estimator (LFE) and curl-based Direct Inversion (c-DI)...
March 22, 2017: IEEE Transactions on Medical Imaging
Lu Ding, Xose Luis Dean Ben, Neal C Burton, Robert W Sobol, Vasilis Ntziachristos, Daniel Razansky
Accurate extraction of physical and biochemical parameters from optoacoustic images is often impeded due to the use of unrigorous inversion schemes, incomplete tomographic detection coverage or other experimental factors that cannot be readily accounted for during the image acquisition and reconstruction process. For instance, inaccurate assumptions in the physical forward model may lead to negative optical absorption values in the reconstructed images. Any artifacts present in the single wavelength optoacoustic images can be significantly aggravated when performing a two-step reconstruction consisting in acoustic inversion and spectral unmixing aimed at rendering the distributions of spectrally-distinct absorbers...
March 22, 2017: IEEE Transactions on Medical Imaging
Jaewook Shin, Min-Oh Kim, Sungmin Cho, Dong-Hyun Kim
Magnetic resonance electrical property tomography (MREPT) is a technique used to extract the electrical properties of tissues (conductivity in particular) using a magnetic resonance imaging (MRI) system. In this work, we propose an improved data acquisition scheme for electrical property tomography technique by utilizing T2 modulation in fast spin echo (FSE) imaging. This technique was motivated by numerical analysis of conductivity reconstruction in the frequency domain; results reveal the spatial frequency-dependent noise texture of conventional methods...
March 17, 2017: IEEE Transactions on Medical Imaging
Luong Nguyen, A Burak Tosun, Jeffrey Fine, Adrian Lee, D Lansing Taylor, Chakra Chennubhotla
Segmenting a broad class of histological structures in transmitted light and/or fluorescence-based images is a prerequisite for determining the pathological basis of cancer, elucidating spatial interactions between histological structures in tumor microenvironments (e.g. tumor infiltrating lymphocytes), facilitating precision medicine studies with deep molecular profiling, and providing an exploratory tool for pathologists. Our paper focuses on segmenting histological structures in hematoxylin and eosin (H&E) stained images of breast tissues, e...
March 16, 2017: IEEE Transactions on Medical Imaging
Ali-Reza Mohammadi-Nejad, Gholam-Ali Hossein-Zadeh, Hamid Soltanian-Zadeh
Multi-modal data fusion has recently emerged as a comprehensive neuroimaging analysis approach, which usually uses canonical correlation analysis (CCA). However, the current CCA-based fusion approaches face problems like high-dimensionality, multi-collinearity, unimodal feature selection, asymmetry, and loss of spatial information in reshaping the imaging data into vectors. This paper proposes a structured and sparse CCA (ssCCA) technique as a novel CCA method to overcome the above problems. To investigate the performance of the proposed algorithm, we have compared three data fusion techniques: standard CCA; regularized CCA; and ssCCA and evaluated their ability to detect multi-modal data associations...
March 14, 2017: IEEE Transactions on Medical Imaging
David Freese, David Hsu, Derek Innes, Craig Levin
Positron Emission Tomography (PET) relies on accurate timing information to pair two 511 keV photons into a coincidence event. Calibration of time delays between detectors becomes increasingly important as the timing resolution of detector technology improves, as calibration error can quickly become a dominant source of error. Previous work has shown the maximum likelihood estimate of these delays can be calculated by least squares estimation, but that approach is not tractable for complex systems and degrades in the presence of randoms...
March 13, 2017: IEEE Transactions on Medical Imaging
Joanne Bates, Darryl McClymont, Irvin Teh, Peter Kohl, Jurgen Schneider, Vicente Grau
A model of cardiac microstructure and diffusion MRI is presented, and compared with experimental data from ex vivo rat hearts. The model includes a simplified representation of individual cells, with physiologically correct cell size and orientation, as well as intra- to extracellular volume ratio. Diffusion MRI is simulated using a Monte Carlo model and realistic MRI sequences. The results show good correspondence between the simulated and experimental MRI signals. Similar patterns are observed in the eigenvalues of the diffusion tensor, the mean diffusivity (MD) and the fractional anisotropy (FA)...
March 10, 2017: IEEE Transactions on Medical Imaging
Rongjian Li, Tao Zeng, Hanchuan Peng, Shuiwang Ji
Digital reconstruction, or tracing, of 3-dimensional (3D) neuron structure from microscopy images is a critical step toward reversing engineering the wiring and anatomy of a brain. Despite a number of prior attempts, this task remains very challenging, especially when images are contaminated by noises or have discontinued segments of neurite patterns. An approach for addressing such problems is to identify the locations of neuronal voxels using image segmentation methods prior to applying tracing or reconstruction techniques...
March 8, 2017: IEEE Transactions on Medical Imaging
Jurgen Rahmer, Daniel Wirtz, Claas Bontus, Joern Borgert, Bernhard Gleich
method that enables sensitive and fast imaging. It does not require ionizing radiation and thus may be a safe alternative for tracking of devices in the catheterization laboratory. The 3D real-time imaging capabilities of MPI have been demonstrated in vivo and recent improvements in fast online image reconstruction enable almost real-time data reconstruction and visualization. Moreover, based on the use of different magnetic particle types for catheter visualization and blood pool imaging, multi-color MPI enables reconstruction of separate images for the catheter and the vessels from simultaneously measured data...
March 7, 2017: IEEE Transactions on Medical Imaging
Yuri Levin-Schwartz, Vince D Calhoun, Tulay Adali
The extraction of information from multiple sets of data is a problem inherent to many disciplines. This is possible by either analyzing the datasets jointly as in data fusion, or separately and then combining, as in data integration. However, selecting the optimal method to combine and analyze multiset data is an ever-present challenge. The primary reason for this is the difficulty in determining the optimal contribution of each dataset to an analysis as well as the amount of potentially exploitable complementary information among datasets...
March 6, 2017: IEEE Transactions on Medical Imaging
Neeraj Kumar, Ruchika Verma, Sanuj Sharma, Surabhi Bhargava, Abhishek Vahadane, Amit Sethi
Nuclear segmentation in digital microscopic tissue images can enable extraction of high-quality features for nuclear morphometrics and other analysis in computational pathology. Conventional image processing techniques such as Otsu thresholding and watershed segmentation do not work effectively on challenging cases, such as chromatin-sparse and crowded nuclei. In contrast, machine learning-based segmentation can generalize across various nuclear appearances. However, training machine learning algorithms require datasets of images in which a vast number of nuclei have been annotated...
March 6, 2017: IEEE Transactions on Medical Imaging
Ivan Klyuzhin, Vesna Sossi
Quantitative PET imaging often requires correcting the image data for deformable motion. With cyclic motion, this is traditionally achieved by separating the coincidence data into a relatively small number of gates, and incorporating the inter-gate image transformation matrices into the reconstruction algorithm. In the presence of non-cyclic deformable motion, this approach may be impractical due to a large number of required gates. In this work, we propose an alternative approach to iterative image reconstruction with correction for deformable motion, wherein unorganized point clouds are used to model the imaged objects in the image space, and motion is corrected for explicitly by introducing a time-dependency into the point coordinates...
March 2, 2017: IEEE Transactions on Medical Imaging
Gustavo Carneiro, Tingying Peng, Christine Bayer, Nassir Navab
In recently published clinical trial results, hypoxia-modified therapies have shown to provide more positive outcomes to cancer patients, compared with standard cancer treatments. The development and validation of these hypoxia-modified therapies depend on an effective way of measuring tumour hypoxia, but a standardised measurement is currently unavailable in clinical practice. Different types of manual measurements have been proposed in clinical research, but in this paper we focus on a recently published approach that quantifies the number and proportion of hypoxic regions using high resolution (immuno- ) fluorescence (IF) and hematoxylin and eosin (HE) stained images of a histological specimen of a tumour...
March 2, 2017: IEEE Transactions on Medical Imaging
Mathias Schwarz, Dominik Soliman, Murad Omar, Andreas Buehler, Saak Ovsepyan, Juan Aguirre, Vasilis Ntziachristos
Optoacoustic (photoacoustic) dermoscopy offers two principal advantages over conventional optical imaging applied in dermatology. First, it yields high-resolution cross-sectional images of the skin at depths not accessible to other non-invasive optical imaging methods. Second, by resolving absorption spectra at multiple wavelengths, it enables label-free three-dimensional visualization of morphological and functional features. However, the relation of pulse energy to generated bandwidth and imaging depth remains poorly defined...
March 1, 2017: IEEE Transactions on Medical Imaging
Guang-Quan Zhou, Weiwei Jiang, Ka-Lee Lai, Yong-Ping Zheng
This paper presents an automated measurement of spine curvature by using prior knowledge on vertebral anatomical structures in ultrasound volume projection imaging (VPI). This method can be used in scoliosis assessment with free-hand 3-D ultrasound imaging. It is based on the extraction of bony features from VPI images using a newly proposed two-fold thresholding strategy, with information of the symmetric and asymmetric measures obtained from phase congruency. The spinous column profile is detected from the segmented bony regions, and it is further used to extract a curve representing spine profile...
February 24, 2017: IEEE Transactions on Medical Imaging
Bob de Vos, Jelmer Wolterink, Pim de Jong, Tim Leiner, Max Viergever, Ivana Isgum
Localization of anatomical structures is a prerequisite for many tasks in medical image analysis. We propose a method for automatic localization of one or more anatomical structures in 3D medical images through detection of their presence in 2D image slices using a convolutional neural network (ConvNet). A single ConvNet is trained to detect presence of the anatomical structure of interest in axial, coronal, and sagittal slices extracted from a 3D image. To allow the ConvNet to analyze slices of different sizes, spatial pyramid pooling is applied...
February 23, 2017: IEEE Transactions on Medical Imaging
Gaoming Li, Haijun Li, Xiyu Duan, Quan Zhou, Juan Zhou, Thomas Wang
The epithelium is a thin layer of tissue that lines hollow organs, such as colon. Visualizing in vertical cross-sections with sub-cellular resolution is essential to understanding early disease mechanisms that progress naturally in the plane perpendicular to the tissue surface. The dual axes confocal architecture collects optical sections in tissue by directing light at an angle incident to the surface using separate illumination and collection beams to reduce effects of scattering, enhance dynamic range, and increase imaging depth...
February 23, 2017: IEEE Transactions on Medical Imaging
Yuexiang Li, Linlin Shen, Shiqi Yu
Reliable identification of Human Epithelial-2 (HEp-2) cell patterns can facilitate the diagnosis of systemic autoimmune diseases. However, traditional approach requires experienced experts to manually recognize the cell patterns, which suffers from the inter-observer variability. In this paper, an automatic pattern recognition system using fully convolutional network (FCN) was proposed to simultaneously address the segmentation and classification problem of HEp-2 specimen images. The proposed system transforms the residual network (ResNet) to fully convolutional residual network (FCRN) enabling the network to perform semantic segmentation task...
February 22, 2017: IEEE Transactions on Medical Imaging
Geoffrey Jones, Neil Clancy, Yusuf Helo, Simon Arridge, Dan Elson, Danail Stoyanov
Multispectral imaging (MSI) can potentially assist the intra-operative assessment of tissue structure, function and viability, by providing information about oxygenation. In this paper, we present a novel technique for recovering intrinsic MSI measurements from endoscopic RGB images without custom hardware adaptations. The advantage of this approach is that it requires no modification to existing surgical and diagnostic endoscopic imaging systems. Our method uses a radiometric colour calibration of the endoscopic camera's sensor in conjunction with a Bayesian framework to recover a per-pixel measurement of the total blood volume (THb) and oxygen saturation (SO2) in the observed tissue...
February 20, 2017: IEEE Transactions on Medical Imaging
Serena Monti, Sirio Cocozza, Pasquale Borrelli, Sina Straub, Mark E Ladd, Marco Salvatore, Enrico Tedeschi, Giuseppe Palma
Cerebral vein analysis provides a chance to study, from an unusual viewpoint, an entire class of brain diseases, including neurodegenerative disorders and traumatic brain injuries. Manual segmentation approaches can be used to assess vascular anatomy, but they are observer-dependent and time consuming; therefore, automated approaches are desirable, as they also improve reproducibility. In the present work, a new, fully automated algorithm, based on structural, morphological and relaxometric information, is proposed to segment the entire cerebral venous system from MR images...
February 20, 2017: IEEE Transactions on Medical Imaging
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