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Towards improved celiac disease diagnosis

Towards improved celiac disease diagnosis

Andreas Vecsei (ORCID: 0000-0001-6017-4625)
  • Grant DOI 10.55776/KLI429
  • Funding program Clinical Research
  • Status ended
  • Start January 2, 2015
  • End June 1, 2018
  • Funding amount € 265,300
  • Project website

Disciplines

Other Human Medicine, Health Sciences (40%); Computer Sciences (10%); Clinical Medicine (50%)

Keywords

    Celiac disease, Pattern recognition, Endoscopy, Villous atrophy, Automated imag analysis, Children

Abstract Final report

Celiac disease (CD) has a prevalence of 1%. To confirm the diagnosis, children with serologically suspected CD undergo small bowel biopsy. To avoid biopsies but still reliably prove the diagnosis, a variety of new endoscopic techniques including software for the analysis of endoscopic still images has been developed. If automated analysis-software can detect villous atrophy not only in endoscopic still images but in video clips as well, in such cases, a small bowel biopsy could entirely be avoided. The main question we will try to assess is, if such software can be developed and easily integrated into the routine of pediatric endoscopy. Furthermore, we will examine if the narrow band imaging technique, an optical/digital chromoendoscopy, can further improve the reliability of automated analysis. Various feature extraction and classification strategies will be applied for automated differentiation between presence and absence of villous atrophy in the endoscopic video clips. 1

In pediatric celiac disease, having a prevalence of 1%, a biopsy of the small bowel is recommended in the case of unclear serology to clarify diagnosis. The reliability of the corresponding histology findings is problematic due to two reasons: (1) Celiac disease exhibits a so-called patchy distribution in some cases, which means that not the entire mucosa is affected. Misdiagnosis may happen in case the celiac disease affected mucosa areas are missed and biopsies have been taken from healthy areas. (2) Pathological diagnosis of biopsy specimens suffers from high inter- and intra-observer variability. Thus, there is need for observer-independent diagnostic methods for celiac disease. In this project the computer-based analysis of endoscopy still images allowed to reliably detect villous atrophy and as such confirm the diagnosis of celiac disease. Furthermore, an computer-based analysis was also successfully developed for and used on endoscopic video, thus enhancing the accuracy of biopsy targeting on the one hand, on the other hand abandoning the necessity of conducting small bowel biopsy at all when villous atrophy was detected. This new diagnostic approach increases the patients` safety during endoscopy, but also significantly contributes to cost reduction as the entire biopsy diagnostic work-up can be avoided.

Research institution(s)
  • Universität Salzburg - 78%
  • St. Anna Kinderkrebsforschung GmbH - 22%
Project participants
  • Andreas Uhl, Universität Salzburg , associated research partner
International project participants
  • Martin Laaß, Technische Universität Dresden - Germany
  • Edward J. Ciaccio, Columbia University New York - USA

Research Output

  • 208 Citations
  • 17 Publications
Publications
  • 2018
    Title Fisher encoding of convolutional neural network features for endoscopic image classification
    DOI 10.1117/1.jmi.5.3.034504
    Type Journal Article
    Author Wimmer G
    Journal Journal of Medical Imaging
    Pages 034504-034504
    Link Publication
  • 2018
    Title Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis
    DOI 10.1016/j.compbiomed.2018.04.020
    Type Journal Article
    Author Gadermayr M
    Journal Computers in Biology and Medicine
    Pages 221-226
    Link Publication
  • 2016
    Title Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis
    DOI 10.3748/wjg.v22.i31.7124
    Type Journal Article
    Author Gadermayr M
    Journal World Journal of Gastroenterology
    Pages 7124-7134
    Link Publication
  • 2016
    Title Texture Description Using Dual Tree Complex Wavelet Packets
    DOI 10.1007/978-3-319-48890-5_18
    Type Book Chapter
    Author Liedlgruber M
    Publisher Springer Nature
    Pages 181-190
  • 2016
    Title Fully automated decision support systems for celiac disease diagnosis
    DOI 10.1016/j.irbm.2015.09.009
    Type Journal Article
    Author Gadermayr M
    Journal IRBM
    Pages 31-39
  • 2016
    Title Narrow Band Imaging Versus White-Light: What is Best for Computer-Assisted Diagnosis of Celiac Disease?
    DOI 10.1109/isbi.2016.7493282
    Type Conference Proceeding Abstract
    Author Gadermayr M
    Pages 355-359
  • 2016
    Title Incorporating Human Knowledge in Automated Celiac Disease Diagnosis
    DOI 10.1109/ipta.2016.7821009
    Type Conference Proceeding Abstract
    Author Gadermayr M
    Pages 1-6
  • 2016
    Title CNN Transfer Learning for the Automated Diagnosis of Celiac Disease
    DOI 10.1109/ipta.2016.7821020
    Type Conference Proceeding Abstract
    Author Wimmer G
    Pages 1-6
  • 2020
    Title Improving CNN training on endoscopic image data by extracting additionally training data from endoscopic videos
    DOI 10.1016/j.compmedimag.2020.101798
    Type Journal Article
    Author Wimmer G
    Journal Computerized Medical Imaging and Graphics
    Pages 101798
    Link Publication
  • 2017
    Title Evaluation of Domain Specific Data Augmentation Techniques for the Classification of Celiac Disease Using Endoscopic Imagery
    DOI 10.1109/mmsp.2017.8122221
    Type Conference Proceeding Abstract
    Author Wimmer G
    Pages 1-6
  • 2017
    Title Degradation adaptive texture classification for real-world application scenarios
    DOI 10.1134/s1054661817010035
    Type Journal Article
    Author Gadermayr M
    Journal Pattern Recognition and Image Analysis
    Pages 66-81
  • 2017
    Title Convolutional Neural Network Architectures for the Automated Diagnosis of Celiac Disease
    DOI 10.1007/978-3-319-54057-3_10
    Type Book Chapter
    Author Wimmer G
    Publisher Springer Nature
    Pages 104-113
  • 2016
    Title Making texture descriptors invariant to blur
    DOI 10.1186/s13640-016-0116-7
    Type Journal Article
    Author Gadermayr M
    Journal EURASIP Journal on Image and Video Processing
    Pages 14
    Link Publication
  • 2015
    Title Survey on computer aided decision support for diagnosis of celiac disease
    DOI 10.1016/j.compbiomed.2015.02.007
    Type Journal Article
    Author Hegenbart S
    Journal Computers in Biology and Medicine
    Pages 348-358
    Link Publication
  • 2015
    Title Comparing Endoscopic Imaging Configurations in Computer-Aided Celiac Disease Diagnosis
    DOI 10.1109/ipta.2015.7367184
    Type Conference Proceeding Abstract
    Author Gadermayr M
    Pages 446-451
  • 2015
    Title Dealing with Intra-Class and Intra-Image Variations in Automatic Celiac Disease Diagnosis
    DOI 10.1007/978-3-662-46224-9_79
    Type Book Chapter
    Author Gadermayr M
    Publisher Springer Nature
    Pages 461-466
  • 2015
    Title Boosting Small-Data Performance of LBP: A Case Study in Celiac Disease Diagnosis
    DOI 10.1007/978-3-319-19665-7_19
    Type Book Chapter
    Author Gadermayr M
    Publisher Springer Nature
    Pages 224-233

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