In Biomedical optics express
Colonoscopy remains the gold standard investigation for colorectal cancer screening as it offers the opportunity to both detect and resect pre-cancerous polyps. Computer-aided polyp characterisation can determine which polyps need polypectomy and recent deep learning-based approaches have shown promising results as clinical decision support tools. Yet polyp appearance during a procedure can vary, making automatic predictions unstable. In this paper, we investigate the use of spatio-temporal information to improve the performance of lesions classification as adenoma or non-adenoma. Two methods are implemented showing an increase in performance and robustness during extensive experiments both on internal and openly available benchmark datasets.
González-Bueno Puyal Juana, Brandao Patrick, Ahmad Omer F, Bhatia Kanwal K, Toth Daniel, Kader Rawen, Lovat Laurence, Mountney Peter, Stoyanov Danail
2023-Feb-01
