Computer-Aided Kidney Segmentation on Abdominal CT Images

Abstract

In this paper, an effective model-based approach for computer-aided kidney segmentation of abdominal CT images with anatomic structure consideration is presented. This automatic segmentation system is expected to assist physicians in both clinical diagnosis and educational training. The proposed method is a coarse to fine segmentation approach divided into two stages. First, the candidate kidney region is extracted according to the statistical geometric location of kidney within the abdomen. This approach is applicable to images of different sizes by using the relative distance of the kidney region to the spine. The second stage identifies the kidney by a series of image processing operations. The main elements of the proposed system are: 1) the location of the spine is used as the landmark for coordinate references; 2) elliptic candidate kidney region extraction with progressive positioning on the consecutive CT images; 3) novel directional model for a more reliable kidney region seed point identification; and 4) adaptive region growing controlled by the properties of image homogeneity. In addition, in order to provide different views for the physicians, we have implemented a visualization tool that will automatically show the renal contour through the method of second-order neighborhood edge detection. We considered segmentation of kidney regions from CT scans that contain pathologies in clinical practice. The results of a series of tests on 358 images from 30 patients indicate an average correlation coefficient of up to 88% between automatic and manual segmentation.

Anatomical Structures Segmentation by Spherical 3D Ray Casting and Gradient Domain Editing

“…3 shows a representative example. These results are comparable to previously reported methods [11,12,13,14] without their underlying assumptions and with a significant improvement in the running time.…”

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease

“…Although the segmentation and volume measurement of the kidney by this method are straightforward, it is laborious and subject to considerable interobserver variability and error. To overcome some of the limitations of the manual method, groups have developed various automated and semiautomated techniques for the segmentation of kidneys from CT or MR images (23)(24)(25). These methods were primarily designed to segment kidneys of normal morphology and size and are not applicable to ADPKD kidneys that present with a wide range of variations in shape and size.…”

Analysis of Watermarking Techniques for Medical Images Preserving ROI

“…Even if this method depends on a model-based technique, that outperforms threshold-based techniques, but it did not use prior knowledge of the liver shape. Lin et al [31] presented the algorithm to perform segmentation of kidney, based on an adaptive region growing and an elliptical kidney region positioning that used spines as landmark. H. Badakhshannoory and P. Saeedi [32] incorporated a method for liver segmentation.…”