Work

Deep learning vs. conventional methods for automatic quantification of total tumor radioactivity in positron projection images of mouse xenograft tumors

Year: 2022

Type: conference-paper

Source: SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging

DOI: 10.1117/12.2610759

Authors: Kevin C. Ma, Michael V. Green, Elaine Jagoda, Jurgen Seidel, Peter L. Choyke, Baris Turkbey, Stephanie A. Harmon

Institution: National Cancer Institute

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: W4220747232

FWCI:

Cites: 14

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Related to: 10