Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 12, 2020
Cardiac MRI has been widely used for noninvasive assessment of cardiac anatomy and function as well as heart diagnosis. The estimation of physiological heart parameters for heart diagnosis essentially require accurate segmentation of the Left ventric...
Predicting the binding affinity between compounds and proteins with reasonable accuracy is crucial in drug discovery. Computational prediction of binding affinity between compounds and targets greatly enhances the probability of finding lead compound...
Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skeleton estimation, which is also called pose estimation, has attracted lots of interests. For pose esti...
OBJECTIVES: Pneumothorax is the most common and potentially life-threatening complication arising from percutaneous lung biopsy. We evaluated the performance of a deep learning algorithm for detection of post-biopsy pneumothorax in chest radiographs ...
OBJECTIVE: To assess the utility of machine learning algorithms for automatically estimating prognosis in patients with repaired tetralogy of Fallot (ToF) using cardiac magnetic resonance (CMR).
OBJECTIVE: Clinical trials in amyotrophic lateral sclerosis (ALS) continue to rely on survival or functional scales as endpoints, despite the emergence of quantitative biomarkers. Neuroimaging-based biomarkers in ALS have been shown to detect ALS-ass...
In this research, we present a semi-supervised segmentation solution using convolutional autoencoders to solve the problem of segmentation tasks having a small number of ground-truth images. We evaluate the proposed deep network architecture for the ...
BACKGROUND: Melanoma results in the vast majority of skin cancer deaths during the last decades, even though this disease accounts for only one percent of all skin cancers' instances. The survival rates of melanoma from early to terminal stages is mo...
A major challenge in radiomics is assembling data from multiple centers. Sharing data between hospitals is restricted by legal and ethical regulations. Distributed learning is a technique, enabling training models on multicenter data without data lea...
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