A robust real-time abnormal region detection framework from capsule endoscopy images

Yanfen Cheng; Xu Liu; Huiping Li

doi:10.1117/12.813363

13 March 2009 A robust real-time abnormal region detection framework from capsule endoscopy images

Yanfen Cheng, Xu Liu, Huiping Li

Proceedings Volume 7264, Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications; 72640I (2009) https://doi.org/10.1117/12.813363
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

In this paper we present a novel method to detect abnormal regions from capsule endoscopy images. Wireless Capsule Endoscopy (WCE) is a recent technology where a capsule with an embedded camera is swallowed by the patient to visualize the gastrointestinal tract. One challenge is one procedure of diagnosis will send out over 50,000 images, making physicians' reviewing process expensive. Physicians' reviewing process involves in identifying images containing abnormal regions (tumor, bleeding, etc) from this large number of image sequence. In this paper we construct a novel framework for robust and real-time abnormal region detection from large amount of capsule endoscopy images. The detected potential abnormal regions can be labeled out automatically to let physicians review further, therefore, reduce the overall reviewing process. In this paper we construct an abnormal region detection framework with the following advantages: 1) Trainable. Users can define and label any type of abnormal region they want to find; The abnormal regions, such as tumor, bleeding, etc., can be pre-defined and labeled using the graphical user interface tool we provided. 2) Efficient. Due to the large number of image data, the detection speed is very important. Our system can detect very efficiently at different scales due to the integral image features we used; 3) Robust. After feature selection we use a cascade of classifiers to further enforce the detection accuracy.

Citation Download Citation

Yanfen Cheng, Xu Liu, and Huiping Li "A robust real-time abnormal region detection framework from capsule endoscopy images", Proc. SPIE 7264, Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 72640I (13 March 2009); https://doi.org/10.1117/12.813363

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KEYWORDS

Endoscopy

Feature extraction

Image processing

Tumors

Detection and tracking algorithms

Feature selection

Human-machine interfaces

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