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

OBJECTIVE. Diagnostic imaging has traditionally relied on a limited set of qualitative
imaging characteristics for the diagnosis and management of lung cancer. Radiomics—the …

We developed multi-modality radiomic models by integrating information extracted from 18 F-
FDG PET and CT images using feature-and image-level fusions, toward improved prognosis …

To characterize intra-tumor heterogeneity comprehensively, we propose a multi-level fusion
strategy to combine PET and CT information at the image-, matrix-and feature-levels towards …

Quantitative extraction of imaging features from medical scans ('radiomics') has attracted a
lot of research attention in the last few years. The literature has consistently emphasized the …

Background Checkpoint inhibitors provided sustained clinical benefit to metastatic lung
cancer patients. Nonetheless, prognostic markers in metastatic settings are still under …

Purpose Lung cancer represents the first cause of cancer-related death in the world.
Radiomics studies arise rapidly in this late decade. The aim of this review is to identify …

Due to the recent developments of both hardware and software technologies, multimodality
medical imaging techniques have been increasingly applied in clinical practice and …

Radiomics analysis quantifies the interpolation of multiple and invisible molecular features
present in diagnostic and therapeutic images. Implementation of 18-fluorine …

Lung cancer is the most common cancer, worldwide, and a major health issue with a
remarkable mortality rate. 2-[18 F] fluoro-2-deoxy-D-glucose positron emission …