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IEEE Transactions on Medical Imaging

Jin Liu, Jianhua Ma, Yi Zhang, Yang Chen, Jian Yang, Huazhong Shu, Limin Luo, Gouenou Coatrieux, Wei Yang, Qianjin Feng, Wufan Chen
In low dose computed tomography (LDCT) imaging, the data inconsistency of measured noisy projections can significantly deteriorate reconstruction images. To deal with this problem, we propose here a new sinogram restoration approach, the Sinogram- Discriminative Feature Representation (S-DFR) method. Different from other sinogram restoration methods, the proposed method works through a 3-D representation based feature decomposition of the projected attenuation component and the noise component using a well-designed composite dictionary containing atoms with discriminative features...
August 14, 2017: IEEE Transactions on Medical Imaging
Lipeng Ning, Yogesh Rathi
Coherence and causality measures are often used to analyze the influence of one region on another during analysis of functional brain networks. The analysis methods usually involve a regression problem where the signal of interest is decomposed into a mixture of regressor and a residual signal. In this paper, we revisit this basic problem and present solutions that provide the minimal-entropy residuals for different types of regression filters, such as causal, instantaneously causal and noncausal filters. Using optimal prediction theory, we derive several novel frequency-domain expressions for partial coherence, causality and conditional causality analysis...
August 14, 2017: IEEE Transactions on Medical Imaging
Mehran Pesteie, Victoria Lessoway, Purang Abolmaesumi, Robert N Rohling
Accurate identification of the needle target is crucial for effective epidural anesthesia. Currently, epidural needle placement is administered by a manual technique, relying on the sense of feel, which has a significant failure rate. Moreover, misleading the needle may lead to inadequate anesthesia, post dural puncture headaches and other potential complications. Ultrasound offers guidance to the physician for identification of the needle target, but accurate interpretation and localization remain challenges...
August 11, 2017: IEEE Transactions on Medical Imaging
Nora Baka, Sieger Leenstra, Theo van Walsum
Localization of the correct vertebral level for surgical entry during lumbar hernia surgery is not straightforward. In this paper we develop and evaluate a solution using free-hand 2D ultrasound (US) imaging in the operation room (OR). Our system exploits the difference in spinous process shapes of the vertebrae. The spinous processes are pre-operatively outlined and labeled in a lateral lumbar X-ray of the patient. Then, in the OR the spinous processes are imaged with 2D sagittal US, and are automatically segmented and registered with the X-ray shapes...
August 10, 2017: IEEE Transactions on Medical Imaging
W Paul Segars, B M W Tsui, Jing Cai, Fang-Fang Yin, George S K Fung, Ehsan Samei
The four dimensional (4D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated...
August 10, 2017: IEEE Transactions on Medical Imaging
Yuan Gao, Kun Wang, Shixin Jiang, Yuhao Liu, Ting Ai, Jie Tian
No abstract text is available yet for this article.
August 9, 2017: IEEE Transactions on Medical Imaging
Russell Bates, Benjamin Irving, Bostjan Markelc, Jakob Kaeppler, Graham Brown, Ruth J Muschel, Sir Michael Brady, Vicente Grau, Julia A Schnabel
Vasculature is known to be of key biological significance, especially in the study of tumors. As such, considerable effort has been focused on the automated segmentation of vasculature in medical and pre-clinical images. The majority of vascular segmentation methods focus on bloodpool labeling methods, however, particularly in the study of tumors it is of particular interest to be able to visualize both perfused and non-perfused vasculature. Imaging vasculature by highlighting the endothelium provides a way to separate the morphology of vasculature from the potentially confounding factor of perfusion...
August 9, 2017: IEEE Transactions on Medical Imaging
Yang Zhang, Yuexin Guo, Wei-Ning Lee
Plane-wave-based ultrafast imaging has become the prevalent technique for non-conventional ultrasound imaging. The image quality, especially in terms of the suppression of artifacts, is generally compromised by reducing the number of transmissions for a higher frame rate. We hereby propose a new ultrafast imaging framework that reduces not only the side lobe artifacts but also the axial lobe artifacts using combined transmissions with a new coherence-based factor. The results from simulations, in vitro wire phantoms, the ex vivo porcine artery, and the in vivo porcine heart show that our proposed methodology greatly reduced the axial lobe artifact by 25 ± 5 dB compared with coherent plane-wave compounding (CPWC), which was considered as the ultrafast imaging standard, and suppressed side lobe artifacts by 15 ± 5 dB compared with CPWC and coherent spherical-wave compounding (CSWC)...
August 4, 2017: IEEE Transactions on Medical Imaging
Andrey Makeev, Stephen J Glick
Iodinated contrast-enhanced x-ray imaging of the breast has been studied with various modalities including, fullfield digital mammography (FFDM), digital breast tomosynthesis (DBT), and dedicated breast CT (BCT). Contrast imaging with breast CT has a number of advantages over FFDM and DBT including the lack of breast compression, and generation of fully isotropic, three-dimensional reconstructions. Nonetheless, for breast CT to be considered as a viable tool for routine clinical use, it would be desirable to reduce radiation dose...
August 2, 2017: IEEE Transactions on Medical Imaging
Li Zhang, Dana Cobzas, Alan H Wilman, Linglong Kong
We present a comparative study for discriminative anatomy detection in high dimensional neuroimaging data. While most studies solve this problem using mass univariate approaches, recent works show better accuracy and variable selection using a sparse classification model. Two types of image-based regularization methods have been proposed in the literature based on either a Graph Net (GN) model or a total variation (TV) model. These studies showed increased classification accuracy and interpretability of results when using image-based regularization, but did not look at the accuracy and quality of the recovered significant regions...
August 2, 2017: IEEE Transactions on Medical Imaging
Kenneth B Bader, Kevin J Haworth, Adam D Maxwell, Christy K Holland
Histotripsy utilizes focused ultrasound to generate bubble clouds for transcutaneous tissue liquefaction. Image guidance of histotripsy pulses is required to provide spatially resolved monitoring of treatment progress. The aim of this study was to investigate the feasibility of plane wave B-mode and passive cavitation images to be used as binary classifiers of histotripsy-induced liquefaction. Prostate tissue phantoms were exposed to mechanically ablative histotripsy pulses over a range of pulse durations (5 - 20 μs) and peak negative pressures (12 - 23 MPa)...
August 2, 2017: IEEE Transactions on Medical Imaging
Joao Pedrosa, Sandro Queiros, Olivier Bernard, Jan Engvall, Thor Edvardsen, Eike Nagel, Jan Dhooge
Cardiac volume/function assessment remains a critical step in daily cardiology and 3D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In the present work, a fast and fully automatic framework for full cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation...
August 2, 2017: IEEE Transactions on Medical Imaging
Dmitry V Sorokin, Igor Peterlik, Marco Tektonidis, Karl Rohr, Pavel Matula
The analysis of the pure motion of subnuclear structures without influence of the cell nucleus motion and deformation is essential in live cell imaging. In this work, we propose a 2D contour-based image registration approach for compensation of nucleus motion and deformation in fluorescence microscopy time-lapse sequences. The proposed approach extends our previous approach which uses a static elasticity model to register cell images. Compared to that scheme, the new approach employs a dynamic elasticity model for forward simulation of nucleus motion and deformation based on the motion of its contours...
July 31, 2017: IEEE Transactions on Medical Imaging
Jiabei Zheng, Jeffrey A Fessler, Heang-Ping Chan
This paper describes a new image reconstruction method for digital breast tomosynthesis (DBT). The new method incorporates detector blur into the forward model. The detector blur in DBT causes correlation in the measurement noise. By making a few approximations that are reasonable for breast imaging, we formulated a regularized quadratic optimization problem with a data-fit term that incorporates models for detector blur and correlated noise (DBCN). We derived a computationally efficient separable quadratic surrogate (SQS) algorithm to solve the optimization problem that has a non-diagonal noise covariance matrix...
July 27, 2017: IEEE Transactions on Medical Imaging
Yuhe Li, Zhendong Qiao, Shaoqin Zhang, Zhenhuan Wu, Xueqin Mao, Jiahua Kou, Hong Qi
Blood sampling is the most common medical technique, and vessel detection is of crucial interest for automated venipuncture systems. In this study, we propose a new convex-regional-based gradient model that uses contextually related regional information, including vessel width size and gray distribution, to segment and locate vessels in a near-infrared image. A convex function with the interval size of vessel width is constructed and utilized for its edge-preserving superiority. Moreover, white and linear noise independences are derived...
July 27, 2017: IEEE Transactions on Medical Imaging
David Larsson, Jeannette H Spuhler, Sven Petersson, Tim Nordenfur, Massimiliano Colarieti-Tosti, Johan Hoffman, Reidar Winter, Matilda Larsson
The combination of medical imaging with computational fluid dynamics (CFD) has enabled the study of 3D blood flow on a patient-specific level. However, with models based on gated high-resolution data, the study of transient flows, and any model implementation into routine cardiac care, is challenging. The present paper presents a novel pathway for patient-specific CFD modelling of the left ventricle (LV), using 4D transthoracic echocardiography (TTE) as input modality. To evaluate the clinical usability, two sub-studies were performed...
July 21, 2017: IEEE Transactions on Medical Imaging
Arvind Balachandrasekaran, Vincent Magnotta, Mathews Jacob
We introduce a structured low rank matrix completion algorithm to recover a series of images from their undersampled measurements, where the signal along the parameter dimension at every pixel is described by a linear combination of exponentials. We exploit the exponential behavior of the signal at every pixel, along with the spatial smoothness of the exponential parameters to derive an annihilation relation in the Fourier domain. This relation translates to a low-rank property on a structured matrix constructed from the Fourier samples...
July 14, 2017: IEEE Transactions on Medical Imaging
Korbinian Mechlem, Sebastian Ehn, Thorsten Sellerer, Eva Braig, Daniela Munzel, Franz Pfeiffer, Peter B Noel
By acquiring tomographic measurements with several distinct photon energy spectra, spectral computed tomography (spectral CT) is able to provide additional material-specific information compared to conventional CT. This information enables the generation of material selective images, which have found various applications in medical imaging. However, material decomposition typically leads to noise amplification and a degradation of the signal-to-noise ratio. This is still a fundamental problem of spectral CT, especially for low-dose medical applications...
July 13, 2017: IEEE Transactions on Medical Imaging
Ilkay Oksuz, Anirban Mukhopadhyay, Rohan Dharmakumar, Sotirios A Tsaftaris
A fully automated 2D+time myocardial segmentation framework is proposed for Cardiac Magnetic Resonance (CMR) Blood-Oxygen-Level-Dependent (BOLD) datasets. Ischemia detection with CINE BOLD CMR relies on spatiotemporal patterns in myocardial intensity but these patterns also trouble supervised segmentation methods, the de-facto standard for myocardial segmentation in cine MRI. Segmentation errors severely undermine the accurate extraction of these patterns. In this paper we build a joint motion and appearance method that relies on dictionary learning to find a suitable subspace...
July 12, 2017: IEEE Transactions on Medical Imaging
Michael D Ketcha, Tharindu De Silva, Runze Han, Ali Uneri, Joseph Goerres, Matthew Jacobson, Sebastian Vogt, Gerhard Kleinszig, Jeffrey H Siewerdsen
For image-guided procedures, the imaging task is often tied to the registration of intraoperative and preoperative images to a common coordinate system. While the accuracy of this registration is a vital factor in system performance, there is relatively little work that relates registration accuracy to image quality factors such as dose, noise, and spatial resolution. To create a theoretical model for such a relationship, we present a Fisher information approach to analyze registration performance in explicit dependence on the underlying image quality factors of image noise, spatial resolution, and signal power spectrum...
July 11, 2017: IEEE Transactions on Medical Imaging
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