Editorial Board
(Source: Medical Image Analysis)
Source: Medical Image Analysis - April 17, 2018 Category: Radiology Source Type: research
Robust variational segmentation of 3D bone CT data with thin cartilage interfaces
In the future, physicians will utilize patient-specific predictive simulations based on diagnostic imaging data to better treat individual patients. For many clinically relevant scenarios, physiology-based modeling and simulation methods exist today (see, e.g., Formaggia et al., 2009; Wall et al., 2010; Ambrosi et al., 2011; Sazonov et al., 2011; Kamensky et al., 2015; Auricchio et al., 2015; Marsden and Esmaily-Moghadam, 2015; Blanchard et al., 2016). (Source: Medical Image Analysis)
Source: Medical Image Analysis - April 16, 2018 Category: Radiology Authors: Tarun Gangwar, Jeff Calder, Takashi Takahashi, Joan E. Bechtold, Dominik Schillinger Source Type: research
A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images
In radiation therapy, heart motion characterization can provide useful information for analyzing the risk of radiation-induced cardiotoxicity and establishing motion management strategies for optimized treatment delivery. Magnetic resonance imaging (MRI)-guided radiation therapy systems provide on-board cine images and allow systematic and quantitative investigations of heart motion during radiation treatment (Chen et al., 2015; Huang et al., 2015; Weygand et al., 2016). Manual delineation of heart contours is time-consuming and therefore not practically feasible for clinical workflows. (Source: Medical Image Analysis)
Source: Medical Image Analysis - April 6, 2018 Category: Radiology Authors: Jian Wu, Thomas R. Mazur, Su Ruan, Chunfeng Lian, Nalini Daniel, Hilary Lashmett, Laura Ochoa, Imran Zoberi, Mark A. Anastasio, H. Michael Gach, Sasa Mutic, Maria Thomas, Hua Li Source Type: research
A Deep Boltzmann Machine-Driven Level Set Method for Heart Motion Tracking Using Cine MRI Images
In radiation therapy, heart motion characterization can provide useful information for analyzing the risk of radiation-induced cardiotoxicity and establishing motion management strategies for optimized treatment delivery. Magnetic resonance imaging (MRI)-guided radiation therapy systems provide on-board cine images and allow systematic and quantitative investigations of heart motion during radiation treatment (Chen et al., 2015; Huang et al., 2015; Weygand et al., 2016). Manual delineation of heart contours is time-consuming and therefore not practically feasible for clinical workflows. (Source: Medical Image Analysis)
Source: Medical Image Analysis - April 6, 2018 Category: Radiology Authors: Jian Wu, Thomas R. Mazur, Su Ruan, Chunfeng Lian, Nalini Daniel, Hilary Lashmett, Laura Ochoa, Imran Zoberi, Mark A. Anastasio, H. Michael Gach, Sasa Mutic, Maria Thomas, Hua Li Source Type: research
Personalized Computational Modeling of Left Atrial Geometry and Transmural Myofiber Architecture
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by uncoordinated atrial activation with consequent deterioration of mechanical function. Affecting an estimated 33 million people worldwide (Rahman et al., 2014), AF is the most common arrhythmia and associated with an increased long-term risk of other cardiovascular diseases. Personalized computational modeling provides a novel framework for integrating and interpreting the role of electrophysiology (EP) in the development and progression of AF (Trayanova, 2014; Trayanova and Chang, 2016). (Source: Medical Image Analysis)
Source: Medical Image Analysis - April 5, 2018 Category: Radiology Authors: Thomas E Fastl, Catalina Tobon-Gomez, Andrew Crozier, John Whitaker, Ronak Rajani, Karen P McCarthy, Damian Sanchez-Quintana, Siew Y Ho, Mark D O ’Neill, Gernot Plank, Martin J Bishop, Steven A Niederer Source Type: research
Statistical testing and power analysis for brain-wide association study
The human brain connectome is usually modeled as a network. In the brain ’s network, accurately locating the connectivity variations associated with phenotypes, such as clinical symptoms, is critical for neuroscientists. With the development of neuroimaging technology and an increasing number of publicly available datasets, such as the 1000 Functional Connectomes Proje ct (FCP) (Biswal et al., 2010), Human Connectome Project (HCP) (Glasser et al., 2016) and UK-Biobank (Miller et al., 2016), large-scale, image-based association studies have become possible and should help us improve our understanding of human brain ...
Source: Medical Image Analysis - April 4, 2018 Category: Radiology Authors: Weikang Gong, Lin Wan, Wenlian Lu, Liang Ma, Fan Cheng, Wei Cheng, Stefan Gr ünewald, Jianfeng Feng Source Type: research
Statistical testing and power analysis for brain-wide association study
The human brain connectome is usually modelled as a network. In the brain ’s network, accurately locating the connectivity variations associated with phenotypes, such as clinical symptoms, is critical for neuroscientists. With the development of neuroimaging technology and an increasing number of publicly available datasets, such as the 1000 Functional Connectomes Proje ct (FCP) Biswal et al. (2010), Human Connectome Project (HCP) Glasser et al. (2016) and UK-Biobank Miller et al. (2016), large-scale, image-based association studies have become possible and should help us improve our understanding of human brain funct...
Source: Medical Image Analysis - April 4, 2018 Category: Radiology Authors: Weikang Gong, Lin Wan, Wenlian Lu, Liang Ma, Fan Cheng, Wei Cheng, Stefan Gr ünewald, Jianfeng Feng Source Type: research
Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease
Alzheimer ’s disease (AD) is a chronic neurodegenerative disease that usually starts slowly and gets worse over time. It is the most common cause of dementia among older adults. It is reported that AD accounts for 60–80 percent of dementia cases (Burns and Iliffe, 2009). In 2015, there were approximate ly 29.8 million people worldwide with AD, and causes about 1.9 million death (Vos et al., 2016). Dementia is the loss of cognitive functioning (e.g., thinking, remembering and reasoning) and behavioral abilities, which often causes a severe burden on the patient and caregiver, including social, ps ychological, physi...
Source: Medical Image Analysis - April 3, 2018 Category: Radiology Authors: Biao Jie, Mingxia Liu, Dinggang Shen Source Type: research
Integration of Temporal and Spatial Properties of Dynamic Connectivity Networks for Automatic Diagnosis of Brain Disease
Alzheimer ’s disease (AD) is a chronic neurodegenerative disease that usually starts slowly and gets worse over time. It is the most common cause of dementia among older adults. It is reported that AD accounts for 60 to 80 percent of dementia cases (Burns and Iliffe, 2009). In 2015, there were approximatel y 29.8 million people worldwide with AD, and causes about 1.9 million death (Vos et al., 2016). Dementia is the loss of cognitive functioning (e.g., thinking, remembering and reasoning) and behavioral abilities, which often causes a severe burden on the patient and caregiver, including social, psy chological, physic...
Source: Medical Image Analysis - April 3, 2018 Category: Radiology Authors: Biao Jie, Mingxia Liu, Dinggang Shen Source Type: research
Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
Facilitating video-assisted surgeries belongs to main objectives for developing next-generation operating theaters. During the surgery, a surgeon controls surgical instruments either robotically or manually. Minimally invasive surgeries and microsurgeries involve vision sensors that help surgeons correctly position the instruments onto operated tissue areas. Carrying out the surgeries is not easy though. In minimally invasive surgeries the surgeons insert elongated surgical instruments through keyhole incisions in the body thereby compromising the dexterity of maneuvers within the body. (Source: Medical Image Analysis)
Source: Medical Image Analysis - March 30, 2018 Category: Radiology Authors: Daniel Wesierski, Anna Jezierska Source Type: research
Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image
Computed tomography (CT) and structural magnetic resonance (MR) images are both important and widely applied in the treatment planning of radiotherapy (Balter et al., 1998; Chen et al., 2004; Khoo et al., 1997; Schad et al., 1987). Recently, it has become desirable to synthesize CT image from the corresponding MR scan. For example, quantitative positron emission tomography (PET) requires CT image for attenuation correction (Carney et al., 2006; Kinahan et al., 1998; Pan et al., 2005). The approach for CT-based attenuation correction is to transform the CT image, which is expressed in Hounsfield units, into an estim...
Source: Medical Image Analysis - March 29, 2018 Category: Radiology Authors: Lei Xiang, Qian Wang, Dong Nie, Lichi Zhang, Xiyao Jin, Yu Qiao, Dinggang Shen Source Type: research
