Work

FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images

Year: 2024

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-031-72390-2_51

Authors: Yiqing Shen, Jingxing Li, Xinyuan Shao, Blanca Inigo Romillo, Ankush Jindal, David Dreizin, Mathias Unberath

Institutions: Johns Hopkins University, University of Maryland, Baltimore

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Institutes of Health, National Institute of General Medical Sciences

Awards: G5520316217, Human-centered CT-based CADx Tools for Traumatic Torso Hemorrhage

OpenAlex ID: W4403649862

FWCI: 6.541

Cites: 27

Cited by: 31

Related to: 10