Automatic Segmentation in Abdominal CT Imaging for the KiTS21 Challenge

Jimin Heo

Keywords: KiTS21 Challenge, 3D Encoder-Decoder, U-Net, Medical Imaging

Abstract: With the KiTS21 Grand Challenge, I propose the automatic segmentation model between the kidney and the mass of the kidney which includes tumor and cyst. Convolutional Neural Network is trained in patches of three-dimensional abdominal CT imaging. For the segmentation of the 3D image, a variant of U-Net which consists of 3D Encoder-Decoder CNN architecture with additional Skip Connection is used. Lastly, there is a loss function to resolve the class imbalance problem frequently occurring in the task of medical imaging. Sørensen-Dice Score and Surface Dice Score on the validation are 82.52 and 70.45.