Asistenční systém pro detekci polypů v reálném čase na bázi konvoluční neuronové sítě

Title in English Assistance system for real-time polyp detection based on convolutional neural network

KVAK Daniel KVAKOVÁ Karolína

Year of publication 2021
Type Article in Periodical
Magazine / Source Gastroenterologie a Hepatologie
Keywords polyp detection, convolutional neural network, artificial intelligence, spatial location
Description The use of artificial intelligence as an assistive detection method in endoscopy has attracted increasing interest in recent years. Machine learning algorithms promise to improve the efficiency of polyp detection and even optical localization of findings, all with minimal training of the endoscopist. The practical goal of this study is to analyse the CAD software (computer-aided diagnosis) Carebot for colorectal polyp detection using a convolutional neural network. The proposed binary classifier for polyp detection achieves accuracy of up to 98%, specificity of 0.99 and precision of 0.96. At the same time, the need for the availability of large-scale clinical data for the development of artificialintelligence- based models for the automatic detection of adenomas and benign neoplastic lesions is discussed.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.