International journal of computer assisted radiology and surgery
Jun 12, 2020
PURPOSE: Guidance and quality control in orthopedic surgery increasingly rely on intra-operative fluoroscopy using a mobile C-arm. The accurate acquisition of standardized and anatomy-specific projections is essential in this process. The correspondi...
Computational and mathematical methods in medicine
Jun 11, 2020
This paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims...
Neuroimaging clinics of North America
Jun 10, 2020
Artificial intelligence, specifically machine learning and deep learning, is a rapidly developing field in imaging sciences with the potential to improve the efficiency and effectiveness of radiologists. This review covers common technical terms and ...
Acta radiologica (Stockholm, Sweden : 1987)
Jun 9, 2020
BACKGROUND: Good feature reproducibility enhances model reliability. The manual segmentation of gastric cancer with liver metastasis (GCLM) can be time-consuming and unstable.
Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-trees from image data by, first deriving a graph-based representation o...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jun 8, 2020
OBJECTIVE: To establish a model for predicting the outcome according to the clinical and computed tomography(CT) image data of patients with intracerebral hemorrhage(ICH).
PURPOSE: Coronary artery calcium (CAC) score has shown to be an accurate predictor of future cardiovascular events. Early detection by CAC scoring might reduce the number of deaths by cardiovascular disease (CVD). Automatically excluding scans which ...
PURPOSE: Accurate segmentation of the hippocampus for hippocampal avoidance whole-brain radiotherapy currently requires high-resolution magnetic resonance imaging (MRI) in addition to neuroanatomic expertise for manual segmentation. Removing the need...
Background Deep learning may help to improve computer-aided detection of volume (CADv) measurement of pulmonary nodules at chest CT. Purpose To determine the efficacy of a deep learning method for improving CADv for measuring the solid and ground-gla...
In this paper, we demonstrate the feasibility and performance of deep residual neural networks for volumetric segmentation of irreversibly damaged brain tissue lesions on T1-weighted MRI scans for chronic stroke patients. A total of 239 T1-weighted M...
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