Abstract: Hyperspectral imaging technology is considered a new paradigm for high-precision pathological image segmentation due to its ability to obtain spatial and spectral information of the detected ...
Abstract: Unsupervised brain lesion segmentation, focusing on learning normative distributions from images of healthy subjects, are less dependent on lesion-labeled data, thus exhibiting better ...
Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...
ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...
1 School of Biomedical Engineering, Sichuan University, Chengdu, China 2 National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China ...
CVPR 2025 Highlight TL;DR: We present CUPS, a Scene-Centric Unsupervised Panoptic Segmentation method leveraging motion and depth from stereo pairs to generate pseudo-labels. Using these labels, we ...
1 Doctoral School of Mathematics and Computer Science, Dakar, Senegal. 2 Research Laboratory in Digital Science and Technology, Multinational Higher School of Telecommunications, Dakar, Senegal. The ...