Work

Uncertainty-aware segmentation of the cervical cancer high-risk clinical target volume from T2-weighted MRI using evidential deep learning

Year: 2025

Type: conference-paper

Source: SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling

DOI: 10.1117/12.3048570

Authors: Gayoung Kim, Akila N. Viswanathan, Rohini Bhatia, Yosef Landman-Gigi, Ehud J. Schmidt, Junghoon Lee

Institution: Johns Hopkins University

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4409230818

FWCI: 0.781

Cites: 12

Cited by: 1

Related to: 10