As a crucial step of biological event extraction, event trigger identification has attracted much attention in recent years. Deep representation methods, which have the superiorities of less feature engineering and end-to-end training, show better pe...
Background and Purpose- Selection of patients with acute ischemic stroke for endovascular treatment generally relies on dynamic susceptibility contrast magnetic resonance imaging or computed tomography perfusion. Dynamic susceptibility contrast magne...
BMC medical informatics and decision making
Dec 30, 2019
BACKGROUND: The accelerated growth of elderly population is creating a heavy burden to the healthcare system in many developed countries and regions. Electrocardiogram (ECG) analysis has been recognized as effective approach to cardiovascular disease...
BMC medical informatics and decision making
Dec 30, 2019
BACKGROUND: Fetal heart rate (FHR) monitoring is a screening tool used by obstetricians to evaluate the fetal state. Because of the complexity and non-linearity, a visual interpretation of FHR signals using common guidelines usually results in signif...
PURPOSE: We propose a novel domain-specific loss, which is a differentiable loss function based on the dose-volume histogram (DVH), and combine it with an adversarial loss for the training of deep neural networks. In this study, we trained a neural n...
PURPOSE: Radiation dose to cardiac substructures is related to radiation-induced heart disease. However, substructures are not considered in radiation therapy planning (RTP) due to poor visualization on CT. Therefore, we developed a novel deep learni...
PURPOSE: Filtering measured projections with a particular convolutional kernel is an essential step in analytic reconstruction of computed tomography (CT) images. A tradeoff between noise and spatial resolution exists for different choices of reconst...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dec 28, 2019
Extensive research has been devoted to the segmentation of the coronary artery. However, owing to its complex anatomical structure, it is extremely challenging to automatically segment the coronary artery from 3D coronary computed tomography angiogra...
INTRODUCTION: Longitudinal magnetic resonance imaging (MRI) has an important role in multiple sclerosis (MS) diagnosis and follow-up. Specifically, the presence of new T2-w lesions on brain MR scans is considered a predictive biomarker for the diseas...
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