Technological innovation is rapidly transforming neuro-oncologic surgery, yet a major unmet need remains: translating promising tools into reliable, ...

Abstract: In the field of computer-aided diagnosis, particularly for tumor diseases, segmentation is a prerequisite and primary step. Multi-modality images become essential for achieving accurate ...

Researchers from the University of Tartu Institute of Physics have developed a novel method for enhancing the quality of three-dimensional images by increasing the depth of focus in holograms fivefold ...

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...

InstaDrive, proposed by SJTU researchers, addresses autonomous driving’s tedious annotation and long-tail data issues. It ...

This project implements a 2D pore-throat network extraction algorithm for porous media images. It uses a modified watershed segmentation approach based on Distance Transform and H-maxima markers to ...