Since most Hepatocellular Carcinoma (HCC) typically arises as a consequence of long-term liver damage, the hepatic molecular characteristics are closely related to the occurrence of HCC. Gaining comprehensive information about the location, morpholog...
PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm.
BACKGROUND AND AIMS: The complications of liver cirrhosis occur after long asymptomatic stages of progressive fibrosis and are generally diagnosed late. We aimed to develop a plasma metabolomic-based score tool to predict these events.
OBJECTIVE: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therap...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 16, 2024
Current methods of digital pathological images typically employ small image patches to learn local representative features to overcome the issues of computationally heavy and memory limitations. However, the global contextual features are not fully c...
BACKGROUND/AIMS: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC pa...
PURPOSE: To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC).
Accurate liver tumor segmentation is crucial for aiding radiologists in hepatocellular carcinoma evaluation and surgical planning. While convolutional neural networks (CNNs) have been successful in medical image segmentation, they face challenges in ...
BACKGROUND: Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 26, 2024
BACKGROUND: Automatic segmentation of hepatocellular carcinoma (HCC) on computed tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The aim of this study is to develop a deep learning based network to detect HCC from ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.