Description and Classification of Confocal Endomicroscopic Images for the Automatic Diagnosis of Inflammatory Bowel Disease

Couceiro, S. Micael; Barreto, João Pedro; Freire, Paulo; Figueiredo, Pedro

doi:10.1007/978-3-642-35428-1_18

Cited by 6 publications

(2 citation statements)

References 20 publications

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“…In the gastrointestinal tract, (Couceiro et al, 2012) developed a methodology that employed off-the-shelf algorithms for segmenting and quantifying intestinal crypts in endomicroscopic images as a potential indicator for Inflammatory Bowel Disease. Similarly, (Prieto et al, 2016) employed crypt detection as a first step towards automated classification between benign and dysplastic epithelial tissue in colorectal polyps.…”

Section: Quantificationmentioning

confidence: 99%

“…examined the variability in stained cardiac tissue structures imaged through FBEµ as a means for intraoperatively identifying nodal tissue in living rat hearts with potential application to neonatal open-heart surgery. In the orapharyngeal tract,(Mualla et al, 2014) identified the borders and locations respectively of epithelial cells in the mucosa layer of vocal chords as the first step to analysing and quantifying structural changes.In the gastrointestinal tract,(Couceiro et al, 2012) developed a methodology that employed off-the-shelf algorithms for segmenting and quantifying intestinal crypts in endomicroscopic images as a potential indicator for Inflammatory Bowel Disease. Similarly,(Prieto et al, 2016) employed crypt detection as a first step towards automated classification between benign and dysplastic epithelial tissue in colorectal polyps (Boschetto et al, 2015a;Boschetto et al, 2016b;Boschetto et al, 2015b).…”

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confidence: 99%

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Image computing for fibre-bundle endomicroscopy: A review

Perperidis¹,

Dhaliwal²,

McLaughlin³

et al. 2020

Medical Image Analysis

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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.

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Section: Quantificationmentioning

confidence: 99%

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confidence: 99%