Radiomics and Deep Learning: Hepatic Applications
Hyo Jung Park, Bumwoo Park, Seung Soo Lee
Abstract
Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hypertension, characterizing focal hepatic lesions, prognosticating malignant hepatic tumors, and segmenting the liver and liver tumors. In this review, we outline the basic technical aspects of radiomics and deep learning and summarize recent investigations of the application of these techniques in liver disease.
Topics & Concepts
MedicineRadiomicsDeep learningRadiologyLiver diseaseMagnetic resonance imagingPathologyMedical physicsArtificial intelligenceInternal medicineComputer scienceRadiomics and Machine Learning in Medical ImagingHepatocellular Carcinoma Treatment and PrognosisAdvanced X-ray and CT Imaging