AIMS: Accurate cancer subtype classification is critical due to variations in tumor progression and prognosis. Traditionally, pathologists classified subtypes manually by examining pathological slides under the microscope. To address increasing workl...
BACKGROUND: Organoids have attracted enormous interest in disease modeling, drug screening, and precision medicine. However, developing robust patient-derived organoids (PDOs) was time-consuming, costly, and had low success rates for certain cancer t...
OBJECTIVES: Due to easy accessibility, the retina is considered a window to the brain. Recent studies have reported retinal vascular abnormalities in bipolar disorder. Deep learning analysis, an advanced computational approach, has been implemented i...
Brain tumors, particularly glioblastoma multiforme, are considered one of the most threatening types of tumors in neuro-oncology. Segmenting brain tumors is a crucial part of medical imaging. It plays a key role in diagnosing conditions, planning tre...
This study aimed to develop a model for predicting the bladder volume ratio between daily CBCT and CT to determine adequate bladder filling in patients undergoing treatment for prostate cancer with external beam radiation therapy (EBRT). The model wa...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2025
In the Domain Generalizable Person Re-Identification (DG Re-ID) task, the quality of identity-relevant descriptor is crucial for domain generalization performance. However, for hard-matching samples, it is difficult to separate high-quality identity-...
Cardiovascular revascularization medicine : including molecular interventions
Mar 7, 2024
BACKGROUND: Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatment of aortic stenosis. Computed tomography (CT) analysis is essential for pre-procedural planning. Currently available software packages for TAVR plann...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
The Bayesian method is capable of capturing real-world uncertainties/incompleteness and properly addressing the overfitting issue faced by deep neural networks. In recent years, Bayesian neural networks (BNNs) have drawn tremendous attention to artif...
BACKGROUND: The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. Still, current image segmentation platforms do not provide the required functionalities for plain setup of medi...
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Nov 2, 2020
PURPOSE: The primary objective of this work was to implement and evaluate a cardiac atlas-based autosegmentation technique based on the "Workflow Box" software (Mirada Medical, Oxford UK), in order to delineate cardiac substructures according to Euro...
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