A multi-paradigm evaluation spanning pixels to voxels for deep learning-based kidney tumor segmentation.

Lalwani R, Telang A, Tiwari V

DOI: 10.1080/03091902.2026.2651078
Published: 2026 May
Container: Journal of medical engineering & technology
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1080/03091902.2026.2651078,
  title = {A multi-paradigm evaluation spanning pixels to voxels for deep learning-based kidney tumor segmentation.},
  author = {Lalwani R and Telang A and Tiwari V},
  year = {2026},
  journal = {Journal of medical engineering \& technology},
  doi = {10.1080/03091902.2026.2651078},
  url = {https://doi.org/10.1080/03091902.2026.2651078}
}

RIS

TY  - JOUR
TI  - A multi-paradigm evaluation spanning pixels to voxels for deep learning-based kidney tumor segmentation.
AU  - Lalwani R
AU  - Telang A
AU  - Tiwari V
PY  - 2026
JO  - Journal of medical engineering & technology
DO  - 10.1080/03091902.2026.2651078
UR  - https://doi.org/10.1080/03091902.2026.2651078
ER  -

APA

R, L., A, T., & V, T. (2026). A multi-paradigm evaluation spanning pixels to voxels for deep learning-based kidney tumor segmentation.. Journal of medical engineering & technology. https://doi.org/10.1080/03091902.2026.2651078

Source records

pubmed · retrieved 2026-09-26T11:12:20.052Z