Transformer-Convolution Pyramid Network for Multi-Class Kidney, Tumor, and Cyst Segmentation

Background/Objectives: Chronic kidney diseases are fatal disorders, and early treatment is crucial for reducing mortality. Segmenting kidneys, tumors, and cysts from computed tomography scans has a significant role in assessing these diseases' progression, determining their severity, and planning surgeries. However, accurate segmentation is challenging for many reasons. The objective of this study is to develop a hybrid network that can overcome these challenges.