Segmentation of Kidneys and Abdominal Images in Mobile Devices with the Android Operating System by Using the Connected Component Labeling Method

Abstract

The purpose of this study was the segmentation of kidneys and abdominal images to assist the diagnosis and to focus on the required area. Kidney segmentation from abdominal images is not an easy task due to the proximity of those organs in the image, the similarity of organ tissues and the occurrence of different properties of the image in each cross-section. In this study, a fully automatic approach was suggested for the kidney segmentation in abdominal computed tomography (CT) images. Both the success of the suggested approach was tested and the performance of the process was evaluated. Area Error Rate (AER) criteria were used to reveal the accuracy of the segmentation operation. Because the vertebral column was used as the reference in the suggested approach, the coordinates of the vertebral column were determined by applying pre-processing to the images. In the second step, the kidney areas were obtained using the Connected Component Labeling (CCL) method. The final step of the study included transferring the operations performed on a PC to a mobile platform. The results obtained reveal that the suggested methodology is a kidney segmentation process that experts can use.