Bladder Segmentation to Classify the Level of Tumor Invasions According to VI-RADS

This is an interdisciplinary project that aims to classify the degree to which of bladder lesions invade the bladder walls, which is critical to assessing the patient’s treatment.

The project is inpired by  VI-RADS (a standardization of MRI acquisition and interpretation that yields a score in range [1, 5]) that has been shown to be effective in medical studies.

In this project, deep learning methods will be explored as a classifier of the scale of bladder lesions. It includes elicitation sessions with radiologists.

This project started as a Cmpe491 project in 2021 Fall semester.