Automated detection of fundic gland polyps from endoscopic images using SSD

Nagito Shichi; Arata Totsuka; Junichi Hasegawa; Tomoyuki Shibata

doi:10.1117/12.2521431

22 March 2019 Automated detection of fundic gland polyps from endoscopic images using SSD

Nagito Shichi, Arata Totsuka, Junichi Hasegawa, Tomoyuki Shibata

Author Affiliations +

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110492O (2019) https://doi.org/10.1117/12.2521431
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

In stomach lesion screening, endoscopic images provide the most effective diagnostic information. However, in the most of lesions at the initial stage, the sign of existence is hard to appear on endoscopic images, and also there is the difference in operations of endoscopes and observation of images in real time among individual medical doctors. Therefore, development of a computer aided diagnostic system (CAD system) for endoscopic images is required. In this study, we propose a method for automated detection of fundic gland polyps from endoscopic images using an object detection algorithm named SSD (Single Shot MultiBox Detector) which is one of CNN (Convolutional Neural Network). SSD used here has 20 of convolution layers and 6 of pooling layers, and the input image size is 300x300. In the experiment, 73 practical fundic gland polyp images were used. To compensate for lack of training images, augmentation was performed using image rotation and edge enhancement. We trained 8751 training images and 2188 verification images. Also, as a preprocessing, highlight areas were removed automatically from all images including both training and test samples. As a result, 94.7% of TP (true positive) rate for 73 fundic gland polyp images was obtained by using our learned SSD.

Citation Download Citation

Nagito Shichi, Arata Totsuka, Junichi Hasegawa, and Tomoyuki Shibata "Automated detection of fundic gland polyps from endoscopic images using SSD", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110492O (22 March 2019); https://doi.org/10.1117/12.2521431

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