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Langerhans Islet Volume Estimation from 3D Optical Projection Tomography

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Computer Vision – ACCV 2016 Workshops (ACCV 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10117))

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Abstract

This paper concerns the comparison of automatic volume estimation methods for isolated pancreatic islets. The estimated islet volumes are needed during the process of assessing the islet sample quality prior to the islet transplantation. We study several different methods for automatic volume estimation. For this purpose we acquired a set of projections using optical tomography for a sample of an islet population. Based on these projections we estimated the islet volumes using two stereological methods (the automatic Wulfsohn’s method and the manual fakir method, considered to be the ground truth in this study), together with the filtered back projection followed by 3D segmentation. We have also employed two simple methods, currently used in medical practice, based on fitting a sphere or a prolate ellipsoid to a single binarized 2D islet projections.

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References

  1. Alejandro, R., Barton, F.B., Hering, B.J., Wease, S.: Collaborative islet transplant registry investigators: update from the collaborative islet transplant registry. Transplantation 86, 1783–1788 (2008)

    Article  Google Scholar 

  2. Ricordi, C., Gray, D.W., Hering, B.J., et al.: Islet isolation assessment in man and large animals. Acta Diabetol. Lat. 27, 185–195 (1990)

    Article  Google Scholar 

  3. Mulchrone, K.F., Choudhury, K.R.: Fitting an ellipse to an arbitrary shape: implications for strain analysis. J. Struct. Geol. 26, 143–153 (2004)

    Article  Google Scholar 

  4. Girman, P., Kříž, J., Friedmanský, J., Saudek, F.: Digital imaging as a possible approach in evaluation of islet yield. Cell Transplant. 12, 129–133 (2003)

    Article  Google Scholar 

  5. Habart, D., Švihlík, J., Schier, J., et al.: Automated analysis of microscopic images of isolated pancreatic islets. Cell Transplant. 25, 2145–2156 (2016)

    Article  Google Scholar 

  6. Kubínová, L., Janáček, J., Guilak, F., Opatrný, Z.: Comparison of several digital and stereological methods for estimating surface area and volume of cells studied by confocal microscopy. Cytometry 36, 85–95 (1999)

    Article  Google Scholar 

  7. Wulfsohn, D., Gundersen, H.J.G., Jensen, E.B.V., Nyengaard, J.R.: Volume estimation from projections. J. Microsc. 215, 111–120 (2004)

    Article  MathSciNet  Google Scholar 

  8. Nock, R., Nielsen, F.: Statistical region merging. IEEE Trans. Pattern Anal. Mach. Intell. 26, 1452–1458 (2004)

    Article  Google Scholar 

  9. Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., Tinevez, J.Y., White, D.J., Hartenstein, V., Eliceiri, K., Tomancak, P., Cardona, A.: Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012)

    Article  Google Scholar 

  10. Cheddad, A., Svensson, C., Sharpe, J., Georgsson, F., Ahlgren, U.: Image processing assisted algorithms for optical projection tomography. IEEE Trans. Med. Imaging 31, 1–15 (2012)

    Article  Google Scholar 

  11. Li, C., Xu, C., Gui, C., Fox, M.D.: Distance regularized level set evolution and its application to image segmentation. IEEE Trans. Image Process. 19, 3243–3254 (2010)

    Article  MathSciNet  Google Scholar 

  12. Švihlík, J., Kybic, J., Habart, D., Berková, Z., Girman, P., Kříž, J., Zacharovová, K.: Classification of microscopy images of Langerhans islets. In: Sebastien Ourselin, M.A.S. (ed.) Medical Imaging 2014 Image Processing, pp. 1–8. SPIE, Bellingham (2014)

    Google Scholar 

  13. Hlushak, H.: Accuracy evaluation of langerhans islet volume estimation from microscopic images. Master’s thesis, Czech Technical University in Prague (2016)

    Google Scholar 

  14. Janacek, J.: Variance of periodic measure of bounded set with random position. Comment. Math. Univ. Carol. 47, 443–455 (2006)

    MathSciNet  MATH  Google Scholar 

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Acknowledgement

This work has been supported by the grant 14-10440S “Automatic analysis of microscopy images of Langerhans islets” of the Czech Science Foundation and by MEYS (LM2015062 Czech-BioImaging).

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Authors and Affiliations

  1. Biomedical Imaging Algorithms (BIA) Group, Faculty of Electrical Engineering, Department of Cybernetics, Center for Machine Perception, Czech Technical University in Prague, Technická 2, Prague, Czech Republic

    Jan Švihlík, Jan Kybic, Hanna Hlushak & Jiří Dvořák

  2. Institute for Clinical and Experimental Medicine, Vídeňská 1958/9, Prague, Czech Republic

    David Habart

  3. Faculty of Chemical Engineering, Department of Computing and Control Engineering, University of Chemistry and Technology, Technická 5, Prague, Czech Republic

    Jan Švihlík

  4. Faculty of Mathematics and Physics, Department of Probability and Mathematical Statistics, Charles University in Prague, Sokolovská 83, Prague 8, Czech Republic

    Jiří Dvořák

  5. Department of Biomathematics, Institute of Physiology, Czech Academy of Sciences, Vídeňská 1083, Prague, Czech Republic

    Barbora Radochová

Authors
  1. Jan Švihlík
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  2. Jan Kybic
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  3. David Habart
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  4. Hanna Hlushak
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  5. Jiří Dvořák
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  6. Barbora Radochová
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Corresponding author

Correspondence to Jan Švihlík .

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Editors and Affiliations

  1. Institute of Information Science, Academia Sinica, Taipei, Taiwan

    Chu-Song Chen

  2. Tsinghua University, Beijing, China

    Jiwen Lu

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Kai-Kuang Ma

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Švihlík, J., Kybic, J., Habart, D., Hlushak, H., Dvořák, J., Radochová, B. (2017). Langerhans Islet Volume Estimation from 3D Optical Projection Tomography. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10117. Springer, Cham. https://doi.org/10.1007/978-3-319-54427-4_42

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  • DOI: https://doi.org/10.1007/978-3-319-54427-4_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54426-7

  • Online ISBN: 978-3-319-54427-4

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