Quantitative morphometry of the cervix using deep learning and geometric area estimation techniques.
- DOI
- 10.1002/ijgo.71333
- Published
- 2026 Sep 3
- Container
- International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1002/ijgo.71333,
title = {Quantitative morphometry of the cervix using deep learning and geometric area estimation techniques.},
author = {Anantharaju A and Keerthana A and Mishra S and Kala N and Ragunathan R and Sreekumaran Nair N and Gunaseelan K and Pal UM},
year = {2026},
journal = {International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics},
doi = {10.1002/ijgo.71333},
url = {https://doi.org/10.1002/ijgo.71333}
}RIS
TY - JOUR TI - Quantitative morphometry of the cervix using deep learning and geometric area estimation techniques. AU - Anantharaju A AU - Keerthana A AU - Mishra S AU - Kala N AU - Ragunathan R AU - Sreekumaran Nair N AU - Gunaseelan K AU - Pal UM PY - 2026 JO - International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics DO - 10.1002/ijgo.71333 UR - https://doi.org/10.1002/ijgo.71333 ER -
APA
A, A., A, K., S, M., N, K., R, R., N, S. N., K, G., & UM, P. (2026). Quantitative morphometry of the cervix using deep learning and geometric area estimation techniques.. International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics. https://doi.org/10.1002/ijgo.71333
Source records
- pubmed · retrieved 2026-09-24T22:10:07.981Z