Computer-Assisted Pit Pattern Analysis of Colonic Lesions

Haefner, Michael; Liedlgruber, Michael; Puespoek, Andreas; Thomas, Schickmair; Schoefl, Rainer; Wrba, Friedrich; Gangl, Alfred; Uhl, Andreas

doi:10.1016/j.gie.2006.03.651

Cited by 1 publication

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“…Image-feature quantification methods based on texture analysis, 24,50,62,63 fractals, 48 or frequency analysis 28 have been shown, but these methods do not directly quantify colonic crypts morphology. Mophometric methods of analyzing histological sections have also been demonstrated, 25,[46][47][48][49]63,64 including automated segmentation of cellular and crypt features. 47 However, the image properties of photographs of histological sections are vastly different than those of chromoendoscopy and OCT, so those methods are not directly applicable to chromoendoscopy and OCT data.…”

Section: Discussionmentioning

confidence: 99%

Automated quantification of colonic crypt morphology using integrated microscopy and optical coherence tomography

Pan

et al. 2008

J. Biomed. Opt.

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Colonic crypt morphological patterns have shown a close correlation with histopathological diagnosis. Imaging technologies such as high-magnification chromoendoscopy and endoscopic optical coherence tomography (OCT) are capable of visualizing crypt morphology in vivo. We have imaged colonic tissue in vitro to simulate high-magnification chromoendoscopy and endoscopic OCT and demonstrate quantification of morphological features of colonic crypts using automated image analysis. 2-D microscopic images with methylene blue staining and correlated 3-D OCT volumes were segmented using marker-based watershed segmentation. 2-D and 3-D crypt morphological features were quantified. The accuracy of segmentation was validated, and measured features are in agreement with known crypt morphology. This work can enable studies to determine the clinical utility of high-magnification chromoendoscopy and endoscopic OCT, as well as studies to evaluate crypt morphology as a biomarker for colonic disease progression.

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Section: Discussionmentioning

confidence: 99%

Automated quantification of colonic crypt morphology using integrated microscopy and optical coherence tomography

Pan

et al. 2008

J. Biomed. Opt.

View full text Add to dashboard Cite

show abstract

Computer-Assisted Pit Pattern Analysis of Colonic Lesions

Cited by 1 publication

References 0 publications

Automated quantification of colonic crypt morphology using integrated microscopy and optical coherence tomography

Automated quantification of colonic crypt morphology using integrated microscopy and optical coherence tomography

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