CRF formulation of active contour population for efficient three-dimensional neurite tracing

S. Gulyanon, N. Sharifai, M. D. Kim, Akira Chiba, G. Tsechpenakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

We present a conditional random field for three-dimensional neurite tracing, using a population of open curve active contours. We aim at increased robustness under spatially varying neurite-background contrast, and at the same time reducing the computational complexity compared to the state-of-the-art. While most existing active contour based methods perform tracing by evolving multiple snakes along the neurite centerline in a sequential manner, our approach implements a simultaneous evolution, reducing the complexity as we show theoretically in our algorithm analysis and experimentally. Our approach provides increased accuracy in ambiguous regions (e.g., low contrast, neurite bifurcations and crossovers, etc.), by exploiting interactions among spatially neighboring snakes. We illustrate the performance of our method and compare it with existing frameworks using sample volumes of wild-type sensory neurons in the larval Drosophila.

Original languageEnglish (US)
Title of host publication2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE Computer Society
Pages593-597
Number of pages5
Volume2016-June
ISBN (Electronic)9781479923502
DOIs
StatePublished - Jun 15 2016
Event2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic
Duration: Apr 13 2016Apr 16 2016

Other

Other2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
CountryCzech Republic
CityPrague
Period4/13/164/16/16

Fingerprint

Neurites
Neurons
Computational complexity
Snakes
Population
Sensory Receptor Cells
Drosophila

Keywords

  • active contours
  • CRF inference
  • Drosophila
  • neurite tracing

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Gulyanon, S., Sharifai, N., Kim, M. D., Chiba, A., & Tsechpenakis, G. (2016). CRF formulation of active contour population for efficient three-dimensional neurite tracing. In 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings (Vol. 2016-June, pp. 593-597). [7493338] IEEE Computer Society. https://doi.org/10.1109/ISBI.2016.7493338

CRF formulation of active contour population for efficient three-dimensional neurite tracing. / Gulyanon, S.; Sharifai, N.; Kim, M. D.; Chiba, Akira; Tsechpenakis, G.

2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June IEEE Computer Society, 2016. p. 593-597 7493338.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Gulyanon, S, Sharifai, N, Kim, MD, Chiba, A & Tsechpenakis, G 2016, CRF formulation of active contour population for efficient three-dimensional neurite tracing. in 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. vol. 2016-June, 7493338, IEEE Computer Society, pp. 593-597, 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016, Prague, Czech Republic, 4/13/16. https://doi.org/10.1109/ISBI.2016.7493338
Gulyanon S, Sharifai N, Kim MD, Chiba A, Tsechpenakis G. CRF formulation of active contour population for efficient three-dimensional neurite tracing. In 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June. IEEE Computer Society. 2016. p. 593-597. 7493338 https://doi.org/10.1109/ISBI.2016.7493338
Gulyanon, S. ; Sharifai, N. ; Kim, M. D. ; Chiba, Akira ; Tsechpenakis, G. / CRF formulation of active contour population for efficient three-dimensional neurite tracing. 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June IEEE Computer Society, 2016. pp. 593-597
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