SVM based colon polyps classifier in a wireless active stereo endoscope

Abstract

This work focuses on the recognition of three-dimensional colon polyps captured by an active stereo vision sensor. The detection algorithm consists of SVM classifier trained on robust feature descriptors. The study is related to Cyclope, this prototype sensor allows real time 3D object reconstruction and continues to be optimized technically to improve its classification task by differentiation between hyperplastic and adenomatous polyps. Experimental results were encouraging and show correct classification rate of approximately 97%. The work contains detailed statistics about the detection rate and the computing complexity. Inspired by intensity histogram, the work shows a new approach that extracts a set of features based on depth histogram and combines stereo measurement with SVM classifiers to correctly classify benign and malignant polyps.

Classification of Polyps in Endoscopic Images Using Self-Supervised Structured Learning

“…SUPERVISED LEARNING Some machine-learning (ML)-based algorithms are used to classify polyps in endoscopic images. Some methods [6], [7] use stereovision-based 3D object analysis to extract visual features using a Support Vector Machine (SVM) Classifier for Polyp detection and classification and correctly classifies polyps using a robust model.…”

Survey of Computer Vision and Machine Learning in Gastrointestinal Endoscopy

“…The shape is described using convex hull, skeletonization, perimeter based features and contrast feature histograms for mucosal texture classification of polyps using Pentax iScan chromoendoscopy. The readers are referred to following notable works for further incite; [18]- [46] 2) Ulcer Detection (UD): Oesophageal and gastric ulcers are caused as a result of GORD. In the colon ulcerative colitis (a type of IBD) occurs when the lining of the large intestine (colon) and the rectum become inflamed.…”

Toward embedded detection of polyps in WCE images for early diagnosis of colorectal cancer

“…In [6] and [7], a first prototype demonstrator equipped with an active stereo vision sensor was proposed to detect protuberating polyps within the colon. The proposed embedded detection algorithm used a SVM classifier trained on robust 3D feature descriptors.…”

“…In this article, we focus on the 2D analysis of the videoendoscopy images in order to investigate other possibilities than 3D shape characterization of polyps to improve capabilities of WCE. As in [7], a particular attention is given to propose a global detection/classification scheme that can be integrated into the "Cyclope"-WCE architecture shown in figure 3 and more precisely, by taking benefits of the FPGA block.…”