Feb. 14, 2024, 5:46 a.m. | Antoine Habis Roy Rosman Nathanson Vannary Meas-Yedid Elsa D. Angelini Jean-Christophe Olivo-Marin

cs.CV updates on arXiv.org arxiv.org

This paper proposes a dynamic interactive and weakly supervised segmentation method with minimal user interactions to address two major challenges in the segmentation of whole slide histopathology images. First, the lack of hand-annotated datasets to train algorithms. Second, the lack of interactive paradigms to enable a dialogue between the pathologist and the machine, which can be a major obstacle for use in clinical routine.
We therefore propose a fast and user oriented method to bridge this gap by giving the …

algorithms challenges cs.cv datasets dialogue dynamic images interactions interactive major paper segmentation supervision train

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Business Intelligence Analyst Insights & Reporting

@ Bertelsmann | Hilversum, NH, NL, 1217WP