An international research team has built the largest three-dimensional digital library of ants ever assembled, scanning more ...

Abstract: In recent years, deep learning has been widely utilized in the fields of biomedical image segmentation and cellular image analysis. Supervised deep neural networks trained on annotated data ...

In organelle imaging, segmentation aims to accurately delineate pixels or voxels corresponding to target organelles from background, noise, and other cellular structures in microscopy images, thereby ...

Abstract: Accurate segmentation of the tongue is fundamental to tongue diagnosis, yet existing methods are predicated on images captured under standard conditions. In practical tongue diagnosis, such ...

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...

This repository contains the code implementation for the paper RSRefSeg: Referring Remote Sensing Image Segmentation with Foundation Models, developed based on the MMSegmentation project. The current ...

LiDAR (Light Detection and Ranging) is an essential device for capturing the depth information of objects. Unmanned aerial vehicles (UAV) can sense the surrounding environment through LiDAR and image ...

Accurate brain tumour segmentation is critical for diagnosis and treatment planning, yet challenging due to tumour complexity. Manual segmentation is time-consuming and variable, necessitating ...