Abstract
Colorectal cancer is one of the most common types of cancer. The development of this cancer starts with the presence of polyps or neoplastic lesions in the colon which can evolve to malignant processes. When a polyp is detected during endoscopy, a resection is carried out and a biopsy is done afterwards. Sometimes, resections that have been done are not really necessary, performing an unnecessary procedure over the patient. The PhD project presented here aims develop a real-time colon polyp detection, localization and classification system based on Deep Learning techniques. The creation of this system could help endoscopist in the optical diagnosis of colon lesions, giving an observer-independent aid when making decisions over colorectal cancers.
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Nogueira-Rodríguez, A., López-Fernández, H., Glez-Peña, D. (2020). Deep Learning Techniques for Real Time Computer-Aided Diagnosis in Colorectal Cancer. In: Herrera-Viedma, E., Vale, Z., Nielsen, P., Martin Del Rey, A., Casado Vara, R. (eds) Distributed Computing and Artificial Intelligence, 16th International Conference, Special Sessions. DCAI 2019. Advances in Intelligent Systems and Computing, vol 1004. Springer, Cham. https://doi.org/10.1007/978-3-030-23946-6_27
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DOI: https://doi.org/10.1007/978-3-030-23946-6_27
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