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IEEE Transactions on Medical Imaging

Marta Varela, Ross Morgan, Adeline Theron, Desmond Dillon-Murphy, Henry Chubb, John Whitaker, Markus Henningsson, Paul Aljabar, Tobias Schaeffter, Christoph Kolbitsch, Oleg V Aslanidi
Knowledge of atrial wall thickness (AWT) has the potential to provide important information for patient stratification and the planning of interventions in atrial arrhythmias. To date, information about AWT has only been acquired in post-mortem or poor-contrast CT studies, providing limited coverage and highly variable estimates of AWT. We present a novel contrast agent-free MRI sequence for imaging AWT and use it to create personalized AWT maps and a biatrial atlas. A novel black-blood phase-sensitive inversion recovery protocol was used to image 10 volunteers and 2 atrial fibrillation patients, as proof of concept...
April 13, 2017: IEEE Transactions on Medical Imaging
Sharmin Sultana, Jason Blatt, Benjamin Gilles, Tanweer Rashid, Michel Audette
This paper presents a segmentation technique to identify the medial axis and the boundary of cranial nerves. We utilize a 3D deformable 1-simplex discrete contour model to ex-tract the medial axis of each cranial nerve. This contour model represents a collection of 2-connected vertices linked by edges, where vertex position is determined by a Newtonian expression for vertex kinematics featuring internal and external forces, the latter of which include attractive forces towards the nerve medial axis. We exploit multiscale vesselness filtering and minimal path techniques in the medial axis extraction method, which also com-putes a radius estimate along the path...
April 12, 2017: IEEE Transactions on Medical Imaging
Mahsa Dadar, Tharick Pascoal, Sarinporn Manitsirikul, Karen Misquitta, Carmela Tartaglia, John Brietner, Pedro Rosa-Neto, Owen Carmichael, Charles DeCarli, D Louis Collins
Segmentation and volumetric quantification of white matter hyperintensities (WMHs) is essential in assessment and monitoring of the vascular burden in aging and Alzheimer's disease (AD), especially when considering their effect on cognition. Manually segmenting WMHs in large cohorts is technically unfeasible due to time and accuracy concerns. Automated tools that can detect WMHs robustly and with high accuracy are needed. Here we present and validate a fully automatic technique for segmentation and volumetric quantification of WMHs in aging and AD...
April 12, 2017: IEEE Transactions on Medical Imaging
Arash Pourtaherian, Harm Scholten, Lieneke Kusters, Svitlana Zinger, Nenad Mihajlovic, Alexander Kolen, Fei Zou, Gary Ng, Hendrikus Korsten, Peter de With
Ultrasound-guided medical interventions are broadly applied in diagnostics and therapy, e.g. regional anesthesia or ablation. A guided intervention using 2D ultrasound is challenging due to the poor instrument visibility, limited field of view and the multi-fold coordination of the medical instrument and ultrasound plane. Recent 3D ultrasound transducers can improve the quality of the image-guided intervention if an automated detection of the needle is used. In this paper, we present a novel method for detecting medical instruments in 3D ultrasound data that is solely based on image processing techniques and validated on various ex-vivo and in-vivo datasets...
April 7, 2017: IEEE Transactions on Medical Imaging
Mona Omidyeganeh, Yiming Xiao, M Omair Ahmad, Hassan Rivaz
Most strain imaging techniques follow a pipeline strategy: in the first step tissue displacement is estimated from radio-frequency (RF) frames, and in the second step, a spatial derivative operation is applied. There are two main issues that arise from this framework. First, the gradient operation amplifies noise, and therefore, smoothing techniques have to be adopted. Second, strain estimation does not exploit the original RF data. It rather relies solely on the noisy displacement field. In this paper, a novel technique is proposed that utilizes both the displacement field and the RF frames to accurately obtain the strain estimates...
April 6, 2017: IEEE Transactions on Medical Imaging
Jan Ruhaak, Thomas Polzin, Stefan Heldmann, Ivor Simpson, Heinz Handels, Jan Modersitzki, Mattias Paul Heinrich
We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a dense continuous optimization framework. The detection of keypoint correspondences enables robustness against large deformations by jointly optimizing over a large number of potential discrete displacements, whereas the dense continuous registration achieves sub-voxel alignment with smooth transformations. Both steps are driven by the same normalized gradient fields data term...
April 5, 2017: IEEE Transactions on Medical Imaging
Amir Abdi, Christina Luong, Teresa Tsang, John Jue, Dale Hawley, Sarah Fleming, Kenneth Gin, Jody Swift, Robert Rohling, Purang Abolmaesumi
Echocardiography (echo) is a skilled technical procedure that depends on the experience of the operator. The aim of this work is to reduce user variability in data acquisition by automatically computing a score of echo quality for operator feedback. To do this, a deep convolutional neural network model, trained on a large set of samples, was developed for scoring apical four-chamber (A4C) echo. In this research, 6,916 end-systolic echo images were manually studied by an expert cardiologist and were assigned a score between 0 (not acceptable) and 5 (excellent)...
April 4, 2017: IEEE Transactions on Medical Imaging
Wenyuan Qi, Yongyi Yang, Chao Song, Miles Wernick, P Hendrik Pretorius, Michael King
Cardiac SPECT images are known to suffer from both cardiac and respiratory motion blur. In this work, we investigate a 4D reconstruction approach to suppress the effect of respiratory motion in gated cardiac SPECT imaging. In this approach, the sequence of cardiac gated images is reconstructed with respect to a reference respiratory amplitude bin in the respiratory cycle. To combat the challenge of inherent high imaging noise, we utilize the data counts acquired during the entire respiratory cycle by making use of a motion-compensated scheme, in which both cardiac motion and respiratory motion are taken into account...
April 4, 2017: IEEE Transactions on Medical Imaging
Seonyeong Park, Siyong Kim, Byongyong Yi, Geoffrey Hugo, H Michael Gach, Yuichi Motai
Accurate sorting of beam projections is important in four-dimensional Cone Beam Computed Tomography (4D CBCT) to improve the quality of the reconstructed 4D CBCT image by removing motion-induced artifacts. We propose Image Registration-based Projection Binning (IRPB), a novel marker-less binning method for 4D CBCT projections, which combines Intensity-based Feature Point Detection (IFPD) and Trajectory Tracking using Random sample consensus (TTR). IRPB extracts breathing motion and phases by analyzing tissue feature point trajectories...
March 31, 2017: IEEE Transactions on Medical Imaging
Yang Song, Qing Li, Heng Huang, Dagan Feng, Mei Chen, Weidong Cai
Microscopy image classification is important in various biomedical applications, such as cancer subtype identification and protein localization for high content screening. To achieve automated and effective microscopy image classification, the representative and discriminative capability of image feature descriptors is essential. To this end, in this study we propose a new feature representation algorithm to facilitate automated microscopy image classification. In particular, we incorporate Fisher vector (FV) encoding with multiple types of local features that are handcrafted or learned, and we design a separationguided dimension reduction (SDR) method to reduce the descriptor dimension while increasing its discriminative capability...
March 24, 2017: IEEE Transactions on Medical Imaging
Ping Gong, Pengfei Song, Shigao Chen
The development of ultrafast ultrasound imaging offers great opportunities to improve imaging technologies such as shear wave elastography and ultrafast Doppler imaging. In Ultrafast imaging, there are trade-offs among image signal-to-noise ratio (SNR), resolution, and post-compounded frame rate. Various approaches have been proposed to solve this trade-off such as multiplane wave imaging or the attempts of implementing synthetic transmit aperture imaging. In this paper, we propose an Ultrafast Synthetic Transmit Aperture (USTA) imaging technique using Hadamard-encoded virtual sources with overlapping sub-apertures to enhance both image SNR and resolution without sacrificing frame rate...
March 24, 2017: IEEE Transactions on Medical Imaging
Anan Liu, Jinhui Tang, Weizhi Nie, Yuting Su
This paper proposes a multi-grained random fields (MGRF) model for mitosis identification. To deal with the difficulty in hidden state discovery and sequential structure modeling in mitosis sequences only containing gradual visual pattern changes, we design the graphical structure to transform individual sequence into a set of coarse-to-fine grained sequences conveying diverse temporal dynamics. Furthermore, we propose the corresponding probabilistic model for joint temporal learning and feature learning. To deal with the non-convex formulation of MGRF, we decompose model training into two sub-tasks, layerwise sequential learning of both temporal dynamics and visual feature and new layer generation by graph-based sequential grouping, and optimize the model by alternating between them iteratively...
March 23, 2017: 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
Alexey Novikov, David Major, Maria Wimmer, Gert Sluiter, Katja Buhler
We propose an automated pipeline for vessel centerline extraction in 3D computed tomography angiography (CTA) scans with arbitrary fields of view. The principal steps of the pipeline are body part detection, candidate seed selection, segment tracking, which includes centerline extraction, and vessel tree growing. The final tree-growing step can be instantiated in either a semi- or fully-automated fashion. The fully-automated initialization is carried out using a vessel position regression algorithm. Both semi- and fully-automated methods were evaluated on 30 CTA scans comprising neck, abdominal and leg arteries in multiple fields of view...
March 9, 2017: IEEE Transactions on Medical Imaging
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