RATIONALE AND OBJECTIVES: Following autosomal dominant polycystic kidney disease (ADPKD) progression by measuring organ volumes requires low measurement variability. The objective of this study is to reduce organ volume measurement variability on MRI...
OBJECTIVE: Our study aimed to determine whether radiomics models based on contrast-enhanced computed tomography (CECT) have considerable ability to predict serosal involvement in gallbladder cancer (GBC) patients.
Deep neural networks (DNNs) have already impacted the field of medicine in data analysis, classification, and image processing. Unfortunately, their performance is drastically reduced when datasets are scarce in nature (e.g., rare diseases or early-r...
OBJECTIVE: Mapping CT number to material property dominates the proton range uncertainty. This work aims to develop a physics-constrained deep learning-based multimodal imaging (PDMI) framework to integrate physics, deep learning, MRI, and advanced d...
Journal of applied clinical medical physics
Oct 3, 2023
PURPOSE: To validate a novel deep learning-based metal artifact correction (MAC) algorithm for CT, namely, AI-MAC, in preclinical setting with comparison to conventional MAC and virtual monochromatic imaging (VMI) technique.
Journal of chemical information and modeling
Oct 3, 2023
With the development of deep learning, almost all single-domain proteins can be predicted at experimental resolution. However, the structure prediction of multi-domain proteins remains a challenge. Achieving end-to-end protein domain assembly and fur...
Machine learning with deep neural networks (DNNs) is widely used for human activity recognition (HAR) to automatically learn features, identify and analyze activities, and to produce a consequential outcome in numerous applications. However, learning...
Deep-learning approaches with data augmentation have been widely used when developing neuroimaging-based computer-aided diagnosis (CAD) systems. To prevent the inflated diagnostic performance caused by data leakage, a correct cross-validation (CV) me...
Cardiac segmentation from magnetic resonance imaging (MRI) is one of the essential tasks in analyzing the anatomy and function of the heart for the assessment and diagnosis of cardiac diseases. However, cardiac MRI generates hundreds of images per sc...
In recent years, due to the contribution to elucidating the functional mechanisms of miRNAs and lncRNAs, the research on miRNA-lncRNA interaction prediction has increased exponentially. However, the prediction research is challenging in bioinformatic...
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