Tumor-SAM: Segment Anything Model for Semi-automatic Lung Tumor Segmentation in CT.

Xie L, Tong Y, Wu C, Torigian DA, Udupa JK, Wan Y

DOI: 10.1117/12.3087226
Published: 2026
Container: Proceedings of SPIE--the International Society for Optical Engineering
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1117/12.3087226,
  title = {Tumor-SAM: Segment Anything Model for Semi-automatic Lung Tumor Segmentation in CT.},
  author = {Xie L and Tong Y and Wu C and Torigian DA and Udupa JK and Wan Y},
  year = {2026},
  journal = {Proceedings of SPIE--the International Society for Optical Engineering},
  doi = {10.1117/12.3087226},
  url = {https://doi.org/10.1117/12.3087226}
}

RIS

TY  - JOUR
TI  - Tumor-SAM: Segment Anything Model for Semi-automatic Lung Tumor Segmentation in CT.
AU  - Xie L
AU  - Tong Y
AU  - Wu C
AU  - Torigian DA
AU  - Udupa JK
AU  - Wan Y
PY  - 2026
JO  - Proceedings of SPIE--the International Society for Optical Engineering
DO  - 10.1117/12.3087226
UR  - https://doi.org/10.1117/12.3087226
ER  -

APA

L, X., Y, T., C, W., DA, T., JK, U., & Y, W. (2026). Tumor-SAM: Segment Anything Model for Semi-automatic Lung Tumor Segmentation in CT.. Proceedings of SPIE--the International Society for Optical Engineering. https://doi.org/10.1117/12.3087226

Source records

pubmed · retrieved 2026-09-25T04:27:43.616Z