CFT-Triplet: integrating contextual, frequency and textural features for fine-grained pulmonary fissure detection

Li Xu, Yu Jiang, Rong Tao, Nanyu Li, Riqing Chen, Chenhui Su, Guodong Li, Fei Tang

Open source

DOI: 10.3389/frai.2026.1817367
Published: 2026-10-20
Container: Frontiers in Artificial Intelligence
Publisher: Frontiers Media SA
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1817367,
  title = {CFT-Triplet: integrating contextual, frequency and textural features for fine-grained pulmonary fissure detection},
  author = {Li Xu and Yu Jiang and Rong Tao and Nanyu Li and Riqing Chen and Chenhui Su and Guodong Li and Fei Tang},
  year = {2026},
  journal = {Frontiers in Artificial Intelligence},
  doi = {10.3389/frai.2026.1817367},
  url = {https://doi.org/10.3389/frai.2026.1817367}
}

RIS

TY  - JOUR
TI  - CFT-Triplet: integrating contextual, frequency and textural features for fine-grained pulmonary fissure detection
AU  - Li Xu
AU  - Yu Jiang
AU  - Rong Tao
AU  - Nanyu Li
AU  - Riqing Chen
AU  - Chenhui Su
AU  - Guodong Li
AU  - Fei Tang
PY  - 2026
JO  - Frontiers in Artificial Intelligence
DO  - 10.3389/frai.2026.1817367
UR  - https://doi.org/10.3389/frai.2026.1817367
ER  -

APA

Xu, L., Jiang, Y., Tao, R., Li, N., Chen, R., Su, C., Li, G., & Tang, F. (2026). CFT-Triplet: integrating contextual, frequency and textural features for fine-grained pulmonary fissure detection. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2026.1817367

Source records

crossref · retrieved 2026-11-08T13:13:30.708Z