Realsee announced the official opening of Realsee3D, a dataset of 10,000 indoor 3D scenes, for academic research and ...

Researchers at Tsinghua University developed PriorFusion, a unified framework that integrates semantic, geometric, and ...

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 ...

Apple is reportedly close to replacing the Sony-made camera sensors found across today’s iPhone lineup with a fully custom, in-house design. According to new information shared by Fixed Focus Digital, ...

Scientists have created an AI tool that could help doctors identify diseases quickly and accurately using only a small number of medical images. Credit: Victoria Kotlyarchuk/iStock A new artificial ...

Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.

tumor cases and BI-RADS annotations in categories 2, 3, 4, and 5. In addition, the dataset also contains ground truth delineations that divide the BUS images into tumoral and normal regions. If you ...

Introduction: Accurate segmentation of pelvic fractures from computed tomography (CT) is crucial for trauma diagnosis and image-guided reduction surgery. The traditional manual slice-by-slice ...

Research scientists in Switzerland have developed and tested a robust AI model that automatically segments major anatomic structures in MRI images, independent of sequence. This is according to a new ...