Image computing for fibre-bundle endomicroscopy: A review

TL;DR

This review paper discusses the technology, clinical applications, and image processing techniques for fibre-bundle endomicroscopy, highlighting current limitations and future research directions in this emerging imaging modality.

Contribution

It provides a comprehensive overview of image reconstruction, analysis, and inference methods specific to fibre-bundle endomicroscopy, integrating recent advances and identifying future challenges.

Findings

Fibre-bundle endomicroscopy is widely used and clinically approved.

Various image processing algorithms improve image quality and diagnostic accuracy.

Current limitations include inherent image artifacts and the need for advanced algorithms.

Abstract

Endomicroscopy is an emerging imaging modality, that facilitates the acquisition of in vivo, in situ optical biopsies, assisting diagnostic and potentially therapeutic interventions. While there is a diverse and constantly expanding range of commercial and experimental optical biopsy platforms available, fibre-bundle endomicroscopy is currently the most widely used platform and is approved for clinical use in a range of clinical indications. Miniaturised, flexible fibre-bundles, guided through the working channel of endoscopes, needles and catheters, enable high-resolution imaging across a variety of organ systems. Yet, the nature of image acquisition though a fibre-bundle gives rise to several inherent characteristics and limitations necessitating novel and effective image pre- and post-processing algorithms, ranging from image formation, enhancement and mosaicing to pathology detection and quantification. This paper introduces the underlying technology and most prevalent clinical applications of fibre-bundle endomicroscopy, and provides a comprehensive, up-to-date, review of relevant image reconstruction, analysis and understanding/inference methodologies. Furthermore, current limitations as well as future challenges and opportunities in fibre-bundle endomicroscopy computing are identified and discussed.