A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract

In this study, we propose a learning enabled microultrasound ( $mu $ US) system that aims to classify inflamed and non-inflamed bowel tissues. $mu $ US images of the caecum, small bowel and colon were obtained from mice treated with agents to induce inflammation. Those images were then used to train three deep learning networks and to provide a ground truth of inflammation status. The classification accuracy was evaluated using 10-fold evaluation and additional B-scan images. Our deep learning approach allowed robust differentiation between healthy tissue and tissue with early signs of inflammation that is not detectable by current endoscopic methods or by human inspection of the $mu $ US images. The methods may be a foundation for future early GI disease diagnosis and enhanced management with computer-aided imaging.
Source: IEE Transactions on Medical Imaging - Category: Biomedical Engineering Source Type: research