Endoscopy video summarisation using novel relational motion histogram descriptor and semi-supervised clustering

A Survey on Medical Image Analysis in Capsule Endoscopy

BACKGROUND AND OBJECTIVE

Capsule Endoscopy (CE) is a non-invasive, patient-friendly alternative to conventional endoscopy procedure. However, CE produces 6 to 8 hrs long video posing a tedious challenge to a gastroenterologist for abnormality detection. Major challenges to an expert are lengthy videos, need of constant concentration and subjectivity of the abnormality. To address these challenges along with high diagnostic accuracy, design and development of automated abnormality detection system is a must. Machine learning and computer vision techniques are devised to develop such automated systems.

METHODS

Study presents a review of quality research papers published in IEEE, Scopus, and Science Direct database with search criteria as capsule endoscopy, engineering, and journal papers. The initial search retrieved 144 publications. After evaluating all articles, 62 publications pertaining to image analysis are selected.

RESULTS

This paper presents a rigorous review comprising all the aspects of medical image analysis concerning capsule endoscopy namely video summarization and redundant image elimination, Image enhancement and interpretation, segmentation and region identification, Computer-aided abnormality detection in capsule endoscopy, Image and video compression. The study provides a comparative analysis of various approaches, experimental setup, performance, strengths, and limitations of the aspects stated above.

CONCLUSIONS

The analyzed image analysis techniques for capsule endoscopy have not yet overcome all current challenges mainly due to lack of dataset and complex nature of the gastrointestinal tract.

Follow-up on: optimizing lesion detection in small bowel capsule endoscopy and beyond: from present problems to future solutions

This review presents noteworthy advances in clinical and experimental Capsule Endoscopy (CE), focusing on the progress that has been reported over the last 5 years since our previous review on the subject. Areas covered: This study presents the commercially available CE platforms, as well as the advances made in optimizing the diagnostic capabilities of CE. The latter includes recent concept and prototype capsule endoscopes, medical approaches to improve diagnostic yield, and progress in software for enhancing visualization, abnormality detection, and lesion localization. Expert commentary: Currently, moving through the second decade of CE evolution, there are still several open issues and remarkable challenges to overcome.