An optimized multi-task contrastive learning framework for HIFU lesion detection and segmentation

Abstract Accurate detection and segmentation of lesions induced by High-Intensity Focused Ultrasound (HIFU) in medical imaging remain significant challenges in automated disease diagnosis. Traditional methods heavily rely on labeled data, which is often scarce, expensive, and time-consuming to obtai...

Full description

Saved in:
Bibliographic Details
Main Authors: Matineh Zavar, Hamid Reza Ghaffari, Hamid Tabatabaee
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-99783-2
Tags: Add Tag
No Tags, Be the first to tag this record!