Classification of colon polyps in NBI endoscopy using vascularization features

Abstract

The evolution of colon cancer starts with colon polyps. There are two different types of colon polyps, namely hyperplasias and adenomas. Hyperplasias are benign polyps which are known not to evolve into cancer and, therefore, do not need to be removed. By contrast, adenomas have a strong tendency to become malignant. Therefore, they have to be removed immediately via polypectomy. For this reason, a method to differentiate reliably adenomas from hyperplasias during a preventive medical endoscopy of the colon (colonoscopy) is highly desirable. A recent study has shown that it is possible to distinguish both types of polyps visually by means of their vascularization. Adenomas exhibit a large amount of blood vessel capillaries on their surface whereas hyperplasias show only few of them. In this paper, we show the feasibility of computer-based classification of colon polyps using vascularization features. The proposed classification algorithm consists of several steps: For the critical part of vessel segmentation, we implemented and compared two segmentation algorithms. After a skeletonization of the detected blood vessel candidates, we used the results as seed points for the Fast Marching algorithm which is used to segment the whole vessel lumen. Subsequently, features are computed from this segmentation which are then used to classify the polyps. In leave-one-out tests on our polyp database (56 polyps), we achieve a correct classification rate of approximately 90%.

Colonoscopy Image Pre-Processing for the Development of Computer-Aided Diagnostic Tools

“…Subtraction of these two colour spaces enables the detection of specular highlights. This method has been used in investigation [16] with satisfactory results. Therein, the detection of specular highlights based on low saturation of the colour of the highlights is suggested.…”

Automatic Segmentation of Polyps in Colonoscopic Narrow-Band Imaging Data

“…The hysteresis thresholding consists of three steps. First we threshold once (in the same fashion as described in [4]) using the function…”

“…Several groups have researched optical biopsy based on manual annotations of colon polyps in narrow-band imaging (NBI) [4]- [6]. These optical biopsy algorithms have shown much promise, with preliminary results of 80-90% classification accuracy of hyperplastic and adenomatous polyps from NBI images.…”

Polyp Segmentation in NBI Colonoscopy

“…We developed a computer-aided system for the classification of polyps in images acquired by Narrow-Band Imaging [6]. During screening the investigator observes a polyp and activates NBI illumination.…”

“…We formed two test sets for the polyp classification software [6] with images taken from our polyp database which is maintained and extended in cooperation with our medical partners. The database consists of more than 1500 images of varying sizes from 320 polyps observed during routine colonoscopies.…”