BACKGROUND: Accurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high co...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 5, 2024
PURPOSE: To develop and validate a prognostic and predictive model integrating deep learning MRI features and clinical information in patients with stage II nasopharyngeal carcinoma (NPC) to identify patients with a low risk of progression for whom i...
Journal of applied clinical medical physics
Dec 5, 2024
PURPOSE: The training of deep learning (DL) models in medical images requires large amounts of sensitive patient data. However, acquiring adequately labeled datasets is challenging because of the heavy workload of manual annotations and the stringent...
View symmetry has been suggested to be an important intermediate representation between view-specific and view-invariant representations of faces in the human brain. Here, we compared view-symmetry in humans and a deep convolutional neural network (D...
OBJECTIVE: Modic changes (MCs) classification system is the most widely used method in magnetic resonance imaging (MRI) for characterizing subchondral vertebral marrow changes. However, it shows a high degree of sensitivity to variations in MRI becau...
Traditional medical image sensors face multiple challenges. First, these sensors typically rely on large amounts of labeled data, which are time-consuming and costly to obtain. Second, when the data volume and image size are large, traditional sensor...
Availability of large and diverse medical datasets is often challenged by privacy and data sharing restrictions. Successful application of machine learning techniques for disease diagnosis, prognosis, and precision medicine, requires large amounts of...
IEEE journal of biomedical and health informatics
Dec 5, 2024
There are relatively few studies on the multi-coil reconstruction task of existing Magnetic Resonance Imaging (MRI) methods, as there are problems with insufficient reconstruction details, high memory occupation during training, etc. Therefore, a new...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Objective - Medical image segmentation is essential for several clinical tasks, including diagnosis, surgical and treatment planning, and image-guided interventions. Deep Learning (DL) methods have become the state-of-the-art for several image segmen...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing impedes interactions between long-range nodes, hindering the ability of message-passing mechanism-bas...