High-precision liver and tumor segmentation is a cornerstone of digital oncology, yet its clinical deployment remains constrained by two persistent challenges: the scarcity of pixel-level annotations ...

Women's Health may earn commission from the links on this page, but we only feature products we believe in. Why Trust Us? In 2026, the body conversation is shifting fast with GLP-1s on the scene, AI ...

As shown below, the inferred masks predicted by our segmentation model trained by the dataset appear similar to the ground truth masks. This repository contains a curated and enhanced version of brain ...

Abstract: Pinpointing and dividing brain tumors is crucial in the patient’s treatment process. It is necessary to develop techniques for the automatic, precise and interpretable analysis of medical ...

Abstract: Accurate detection of brain tumors is a vital component in medical diagnostics, which is essential for the precise interpretation and analysis of medical imaging results. This method ...

This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual information ...

Brain tumour image segmentation has emerged as a vital task in neuro-oncology, providing precise delineation of tumour boundaries for diagnosis, treatment planning and monitoring. Techniques span ...

A complete image-processing pipeline that combines Fuzzy C-Means (FCM) clustering with Canny edge detection to segment brain tumors in MRI images. The system proposes a hybrid approach — noise removal ...