Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …

Radiomics is a quantitative approach to analyzing medical multi-layered images in
combination with molecular, genetic and clinical information, which has evidenced very …

Objective Robust differentiation between infarcted and normal tissue is important for clinical
diagnosis and precision medicine. The aim of this work is to investigate the radiomic …

Objective To investigate the impact of harmonization on the performance of CT, PET, and
fused PET/CT radiomic features toward the prediction of mutations status, for epidermal …

Background We aimed to analyze the prognostic power of CT-based radiomics models
using data of 14,339 COVID-19 patients. Methods Whole lung segmentations were …

This study aimed to investigate the diagnostic performance of machine learning-based
radiomics analysis to diagnose coronary artery disease status and risk from rest/stress …

Aims Despite the promising results achieved by radiomics prognostic models for various
clinical applications, multiple challenges still need to be addressed. The two main limitations …

Abstract Purpose Glioblastoma Multiforme (GBM) represents the predominant aggressive
primary tumor of the brain with short overall survival (OS) time. We aim to assess the …

The malignant tumors in nature share some common morphological characteristics.
Radiomics is not only images but also data; we think that a probability exists in a set of …

A U-shaped contraction pattern was shown to be associated with a better Cardiac
resynchronization therapy (CRT) response. The main goal of this study is to automatically …