@inproceedings{cbb6418de0474c78b2c49f815eee4b68,
title = "Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery",
abstract = "The main curative treatment for localized colon cancer is surgical resection. However when tumor residuals are left positive margins are found during the histological examinations and additional treatment is needed to inhibit recurrence. Hyperspectral imaging (HSI) can offer non-invasive surgical guidance with the potential of optimizing the surgical effectiveness. In this paper we investigate the capability of HSI for automated colon cancer detection in six ex-vivo specimens employing a spectral-spatial patch-based classification approach. The results demonstrate the feasibility in assessing the benign and malignant boundaries of the lesion with a sensitivity of 0.88 and specificity of 0.78. The results are compared with the state-of-the-art deep learning based approaches. The method with a new hybrid CNN outperforms the state-of the-art approaches (0.74 vs. 0.82 AUC). This study paves the way for further investigation towards improving surgical outcomes with HSI.",
keywords = "hyperspectral imaging, colon cancer, image-guided surgery, 3D-2D CNN, Neoplasm Recurrence, Local/diagnostic imaging, Biopsy, Colonic Neoplasms/diagnostic imaging, Humans, Surgery, Computer-Assisted",
author = "Francesca Manni and Roger Fonoll{\`a} and {van der Sommen}, Fons and Svitlana Zinger and Caifeng Shan and Esther Kho and {Brouwer de Koning}, {Susan G.} and Ruers, {Theo J.M.} and {de With}, {Peter H.N.}",
year = "2020",
month = aug,
day = "27",
doi = "10.1109/EMBC44109.2020.9176543",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "IEEE EMBS",
pages = "1169--1173",
booktitle = "42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society",
}
