Deep learning (DL) architectures have opened new horizons in medical image analysis
attaining unprecedented performance in tasks such as tissue classification and …

Purpose To investigate and histopathologically validate the role of model selection in the
design of novel parametric meta-maps towards the discrimination of low from high-grade soft …

Background Subcutaneous fat may have variable signal intensity on T2w images depending
on the choice of imaging parameters. However, fatty components within tumors have a …

Purpose The purpose of this study was to compare the performance of four diffusion models,
including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion …

Purpose: The proposed study aims to develop an MRI-based radiomics analysis framework
and investigate the feasibility of the calculated quantitative imaging features for …

Medical imaging is an active and developing area, providing significant anatomical,
functional, and molecular information in a wide range of clinical and research studies …

Purpose This study aimed to assess the effect of echo spacing in transverse magnetization
(T2) signal decay of gel and fat (oil) samples. Additionally, we assess the feasibility of using …

Magnetic resonance imaging (MRI) is an imaging technique that is based on the interactions
of water with external magnetic fields. Magnetic properties of water molecules are analyzed …

Diffusion Weighted Imaging (DWI) is a noninvasive imaging technique in Magnetic
Resonance Imaging (MRI), providing significant anatomical and functional information in a …

This paper presents a method for reducing the Diffusion Weighted Magnetic Resonance
Imaging (DW-MRI) examination time based on the mathematical framework of sparse …