Kidney Region of Interest Extraction Based on Iterative Convolution Threshold Method

Abstract

The kidney is one of the essential organs in the human body, and the premise of evaluating kidney function is to obtain kidney segmentation accurately. Some kidney segmentation methods have achieved high segmentation accuracy in the past, but the segmentation rate has also decreased with accuracy. In this paper, based on the renal time-activity curve, an adaptive method is used to determine the time of tracer absorption in kidney and background areas. The iterative convolution threshold method is used to minimize the energy function during kidney segmentation and significantly improve segmentation efficiency. This method analyzes the data of 174 patients using dynamic renal scintigraphy with <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc-DTPA. Compared with the level set Chan-Vese method to minimize the energy function, the number of iterations of the iterative convolution threshold method is only one-third of the level set Chan-Vese method. The computer runtime is only one-fifth of the level set method. The clinical experimental results show that the iterative convolution threshold method has broad application prospects in accurately estimating the glomerular filtration rate in dynamic renal scintigraphy.