A novel hybrid deep learning pipeline for precise segmentation of skin cancer lesions.

Wang XH, Saeed M, Ahmed N, Di WK, Ji XY, Xu PP, Saddozai UAK.

Open source

DOI: 10.3389/fmed.2026.1915861
Published: 2026-08-20
Container: Front Med (Lausanne)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fmed.2026.1915861,
  title = {A novel hybrid deep learning pipeline for precise segmentation of skin cancer lesions.},
  author = {Wang XH and  Saeed M and  Ahmed N and  Di WK and  Ji XY and  Xu PP and  Saddozai UAK.},
  year = {2026},
  journal = {Front Med (Lausanne)},
  doi = {10.3389/fmed.2026.1915861},
  url = {https://doi.org/10.3389/fmed.2026.1915861}
}

RIS

TY  - JOUR
TI  - A novel hybrid deep learning pipeline for precise segmentation of skin cancer lesions.
AU  - Wang XH
AU  -  Saeed M
AU  -  Ahmed N
AU  -  Di WK
AU  -  Ji XY
AU  -  Xu PP
AU  -  Saddozai UAK.
PY  - 2026
JO  - Front Med (Lausanne)
DO  - 10.3389/fmed.2026.1915861
UR  - https://doi.org/10.3389/fmed.2026.1915861
ER  -

APA

XH, W., M, S., N, A., WK, D., XY, J., PP, X., & UAK., S. (2026). A novel hybrid deep learning pipeline for precise segmentation of skin cancer lesions.. Front Med (Lausanne). https://doi.org/10.3389/fmed.2026.1915861

Source records

europe-pmc · retrieved 2026-09-25T21:59:25.153Z
doaj · retrieved 2026-09-25T21:59:25.155Z