Endoscopic measurement of ulcerative colitis (UC) severity is important since endoscopic disease severity may better predict future outcomes in UC than symptoms. However, it is difficult to evaluate the endoscopic severity of UC objectively because of the non-uniform nature of endoscopic features associated with UC, and large variations in their patterns. In this paper, we propose a method to classify UC severity in colonoscopy videos by learning from confusion. The similar looking frames from the colonoscopy videos generate similar features, and the Convolutional Neural Network (CNN) model trained using these similar features is confused. Therefore, it cannot provide accurate classification. By isolating these similar frames (features), we potentially reduce model confusion. We propose a new training strategy to isolate these similar frames (features), and a CNN based method for classifying UC severity in colonoscopy videos using the new training strategy. The experiments show that the proposed method for classifying UC severity increases classification effectiveness significantly.
|Original language||English (US)|
|Title of host publication||Advances in Visual Computing - 17th International Symposium, ISVC 2022, Proceedings|
|Editors||George Bebis, Bo Li, Angela Yao, Yang Liu, Ye Duan, Manfred Lau, Rajiv Khadka, Ana Crisan, Remco Chang|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||13|
|State||Published - 2022|
|Event||17th International Symposium on Visual Computing, ISVC 2022 - San Diego, United States|
Duration: Oct 3 2022 → Oct 5 2022
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||17th International Symposium on Visual Computing, ISVC 2022|
|Period||10/3/22 → 10/5/22|
Bibliographical noteFunding Information:
Conflict of Interest and Acknowledgments. Tavanapong and Oh have equity interest and management roles in EndoMetric Corp. Dr. de Groen serves on the Scientific Advisory Board of EndoMetric Corp. This work is partially supported by the NIH Grant No. 1R01DK106130-01A1. Findings, opinions, and conclusions expressed in this paper do not necessarily reflect the view of the funding agency.
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Learning from confusion
- Medical image classification
- Ulcerative colitis severity