Applied Deep Learning to Identify and Localize Polyps from Endoscopic Images

• URL: http://arxiv.org/abs/2301.09219v1
• Date: Sun, 22 Jan 2023 22:14:25 GMT
• Title: Applied Deep Learning to Identify and Localize Polyps from Endoscopic Images
• Authors: Chandana Raju, Sumedh Vilas Datar, Kushala Hari, Kavin Vijay, Suma Ningappa
• Abstract summary: We have aimed at open sourcing a dataset which contains annotations of polyps and ulcers. This is the first dataset that's coming from India containing polyp and ulcer images. We evaluated our dataset with several popular deep learning object detection models that's trained on large publicly available datasets.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Deep learning based neural networks have gained popularity for a variety of biomedical imaging applications. In the last few years several works have shown the use of these methods for colon cancer detection and the early results have been promising. These methods can potentially be utilized to assist doctor's and may help in identifying the number of lesions or abnormalities in a diagnosis session. From our literature survey we found out that there is a lack of publicly available labeled data. Thus, as part of this work, we have aimed at open sourcing a dataset which contains annotations of polyps and ulcers. This is the first dataset that's coming from India containing polyp and ulcer images. The dataset can be used for detection and classification tasks. We also evaluated our dataset with several popular deep learning object detection models that's trained on large publicly available datasets and found out empirically that the model trained on one dataset works well on our dataset that has data being captured in a different acquisition device.

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