Work

Repurposing traditional U-Net predictions for sparse SAM prompting in medical image segmentation

Year: 2023

Type: article

Source: Biomedical Physics & Engineering Express

DOI: 10.1088/2057-1976/ad17a7

Authors: Zachery Morton Colbert, Daniel Arrington, Matthew Foote, Jonas Gårding, Dominik Fay, Michael Huo, Mark Pinkham, Prabhakar Ramachandran

Institutions: Princess Alexandra Hospital, Elekta (Sweden), KTH Royal Institute of Technology

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

Funder: Elekta Instruments

OpenAlex ID: W4389985451

FWCI: 0.732

Cites: 25

Cited by: 10

Related to: 10