Artificial Intelligence for Segmentation of Bladder Tumor Cystoscopic Images Performed by U-Net with Dilated Convolution.

Early intravesical recurrence after transurethral resection of bladder tumors (TURBT) is often caused by overlooking of tumors during TURBT. Although narrow-band imaging and photodynamic diagnosis were developed to detect more tumors than conventional white-light imaging, the accuracy of these systems has been subjective, along with poor reproducibility due to their dependence on the physician's experience and skills. To create an objective and reproducible diagnosing system, we aimed at assessing the utility of artificial intelligence (AI) with Dilated U-Net to reduce the risk of overlooked bladder tumors when compared with the conventional AI system, termed U-Net.