Simple Summary The proper management of prostate cancer requires accurate assessment
of patients diagnosed with prostate cancer, a common and often lethal cancer. Current …

Deep learning-based methods have achieved encouraging performances in the field of
Magnetic Resonance (MR) image reconstruction. Nevertheless, building powerful and …

Introduction Magnetic resonance imaging (MRI) with its innovative techniques, such as
diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), increases the …

Objective Accurate nidus segmentation and quantification have long been challenging but
important tasks in the clinical management of Cerebral Arteriovenous Malformation (CAVM) …

Volumetric magnetic resonance (MR) image segmentation plays an important role in many
clinical applications. Deep learning (DL) has recently achieved state-of-the-art or even …

Background and purpose Motion estimation from severely downsampled 4D-MRI is
essential for real-time imaging and tumor tracking. This simulation study developed a novel …

Background: The reproducibility of machine-learning models in prostate cancer detection
across different MRI vendors remains a significant challenge. Methods: This study …

Deep learning‐based‐image denoising methods have recently achieved excellent
performance by learning non‐linear mapping in the spatial domain. However, these …

Multi-contrast magnetic resonance imaging (MRI)-based automatic auxiliary glioma
diagnosis plays an important role in the clinic. Contrast-enhanced MRI sequences (eg …

Magnetic Resonance Imaging (MRI) has become an important technique in the clinic for the
visualization, detection, and diagnosis of various diseases. However, one bottleneck …