Article

Developing a Fully Automated Imaging Biomarker for HCC Risk Assessment via MRI-Based Tumor Segmentation and EPM

2025-11-17

Abstract excerpt

<h4>ABSTRACT</h4> This study investigates the feasibility of using automated tumor segmentation as the region of interest for early detection of hepatocellular carcinoma (HCC) using magnetic resonance imaging (MRI). Enhancement Pattern Mapping (EPM) is used as a voxel-wise imaging biomarker within the region of interest once segmentations are generated. We implement PocketNet, a lightweight convolutional neural n...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 43592d6c-8376-527b-9733-da3630923d0b
DOI: 10.1101/2025.11.14.25340275

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Developing a Fully Automated Imaging Biomarker for HCC Risk Assessment via MRI-Based Tumor Segmentation and EPMDOI 10.1101/2025.11.14.25340275Read

Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics.Semantic proximity Read

MRICombo: a deep-learning-based framework for universal volume segmentation, grading-staging, and malignancy detection across heterogeneous MRISemantic proximity Read

Recent Advancements in Grad-CAM and variants: Enhancing Brain Tumor Detection, Segmentation, and ClassificationSemantic proximity Read

Towards Longitudinal Glioma Segmentation: Evaluating combined pre- and post-treatment MRI training data for automated tumor segmentation using nnU-NetSemantic proximity Read

Dual-Encoder Network Optimization for Binary Semantic Segmentation of Focal Liver Lesions (FLLs)Semantic proximity Read

A fully automated hybrid approach to assessing liver fibrosis and necroinflammation on conventional MRI: A multi-center cohort StudySemantic proximity Read

Liver and Focal Lesion Segmentation in Multi-Sequence MRI Enhanced by Cascaded Deep LearningSemantic proximity Read

Multimodal automated diagnosis of lymphovascular invasion in breast cancer on contrast-enhanced MRI: ResUNet++ segmentation and Transformer-based classificationSemantic proximity Read

Liver and Focal Lesion Segmentation in Multi-Sequence MRI Enhanced by Cascaded Deep LearningSemantic proximity Read

DCE-Net: A Dynamic Context Encoder Network for Liver Tumor SegmentationSemantic proximity Read

Deep learning-based MRI model for predicting P53-mutated hepatocellular carcinoma.Semantic proximity Read

Automated differentiation of malignant and benign primary solid liver lesions on MRI: an externally validated radiomics modelSemantic proximity Read