Abstarct: Autosomal dominant polycystic kidney disease (ADPKD) is generally a late-onset congenital disorder characterized by progressive cyst development and bilaterally enlarged kidneys with multiple cysts. The disease often leads to chronic renal failure and may result in total loss of kidney function. In the recent investigations in animal models, it has been shown that maybe it is possible to reduce the speed of progression by medical treatment, so if we could diagnose the progression stages, it would be a cure for ADPKD patients. In order to diagnosing the progression stages of this disease, we should calculate the ratio of the kidney volume to its cysts volume in all of the slices of a kidney and also we should measure the amount of reducing of this ratio in the progression periods of the cysts. Abdomen cavity CT images have been used for automatic calculation of the ratio of the cysts volume to kidney volume. In these images, the kidney and its cysts are extracted first. Kidney segmentation is done by using a combination of three methods: thresholding method, region-baxsed method and model-baxsed method. The principal steps of kidney segmentation of this method is: using the position of spine; dividing slices into two sets; the central slices and the first and the last slices; finding the initial point for Region-Growing algorithm; using the Region-Growing and controlling the algorithm using characteristics such as number of pixels, mean of pixels intensity and improving the kidney region using the results of preceding slice. The proposed method was applied to the 333 images of 22 different patients and the obtained mean value of Dice similarity constant between automatic and manual segmentation for three patients (66 slices) was about 91.84%. Furthermore in quality evaluation of 333 images, 79.8% of them took the grade A. In the CT imaging, the reflection result of the incident ‘X’ beam on the tissue is a voxel with low brightness intensity. Considering this characteristic, the parametric image-baxsed method is used for cyst segmentation. If we extract the cyst tissue in a slice, we examine the same region in the preceding and the following slices to know whether it is a cyst tissue or not. We do this process because we have a mass cyst, so the possibilities of existence of the cyst in the preceding and the following slices in the obtained region are high. At last, we have computed the ratio of the cyst volume to the kidney using the Cavalieri slices. Since the pixels in the CT imaging are well-defined and constant volumes, we have used them for calculating the volume ratio using Cavalieri slices. In this way, a volume ratio in terms of pixel numbers has been obtained.