A 3D primary vessel reconstruction framework with serial microscopy images

Yanhui Liang; Fusheng Wang; Darren Treanor; Derek Magee; George Teodoro; Yangyang Zhu; Jun Kong

doi:10.1007/978-3-319-24574-4_30

A 3D primary vessel reconstruction framework with serial microscopy images

Yanhui Liang
, Fusheng Wang
, Darren Treanor
, Derek Magee
, George Teodoro
, Yangyang Zhu
, Jun Kong

Emory University
Leeds Teaching Hospitals NHS Trust
University of Leeds
Universidade de Brasília
Stony Brook University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscopy images of liver tissue, we identify primary vessels with an improved variational level set framework at each 2D slide. We propose a Vessel Directed Fitting Energy (VDFE) to provide prior information on vessel wall probability in an energy minimization paradigm. We find the optimal vessel cross-section associations along the image sequence with a two-stage procedure. Vessel mappings are first found between each pair of adjacent slides with a similarity function for four association cases. These bi-slide vessel components are further linked by Bayesian Maximum A Posteriori (MAP) estimation where the posterior probability is modeled as a Markov chain. The efficacy of the proposed method is demonstrated with 54 whole slide microscopy images of sequential sections from a human liver.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings
Editors	Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells
Publisher	Springer Verlag
Pages	251-259
Number of pages	9
ISBN (Print)	9783319245737
DOIs	https://doi.org/10.1007/978-3-319-24574-4_30
State	Published - 2015
Event	18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany Duration: Oct 5 2015 → Oct 9 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9351
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Country/Territory	Germany
City	Munich
Period	10/5/15 → 10/9/15

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10.1007/978-3-319-24574-4_30

Cite this

Liang, Y., Wang, F., Treanor, D., Magee, D., Teodoro, G., Zhu, Y., & Kong, J. (2015). A 3D primary vessel reconstruction framework with serial microscopy images. In A. F. Frangi, N. Navab, J. Hornegger, & W. M. Wells (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings (pp. 251-259). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9351). Springer Verlag. https://doi.org/10.1007/978-3-319-24574-4_30

Liang, Yanhui ; Wang, Fusheng ; Treanor, Darren et al. / A 3D primary vessel reconstruction framework with serial microscopy images. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings. editor / Alejandro F. Frangi ; Nassir Navab ; Joachim Hornegger ; William M. Wells. Springer Verlag, 2015. pp. 251-259 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A 3D primary vessel reconstruction framework with serial microscopy images",

abstract = "Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscopy images of liver tissue, we identify primary vessels with an improved variational level set framework at each 2D slide. We propose a Vessel Directed Fitting Energy (VDFE) to provide prior information on vessel wall probability in an energy minimization paradigm. We find the optimal vessel cross-section associations along the image sequence with a two-stage procedure. Vessel mappings are first found between each pair of adjacent slides with a similarity function for four association cases. These bi-slide vessel components are further linked by Bayesian Maximum A Posteriori (MAP) estimation where the posterior probability is modeled as a Markov chain. The efficacy of the proposed method is demonstrated with 54 whole slide microscopy images of sequential sections from a human liver.",

author = "Yanhui Liang and Fusheng Wang and Darren Treanor and Derek Magee and George Teodoro and Yangyang Zhu and Jun Kong",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 ; Conference date: 05-10-2015 Through 09-10-2015",

year = "2015",

doi = "10.1007/978-3-319-24574-4\_30",

language = "English",

isbn = "9783319245737",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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}

Liang, Y, Wang, F, Treanor, D, Magee, D, Teodoro, G, Zhu, Y & Kong, J 2015, A 3D primary vessel reconstruction framework with serial microscopy images. in AF Frangi, N Navab, J Hornegger & WM Wells (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9351, Springer Verlag, pp. 251-259, 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, Munich, Germany, 10/5/15. https://doi.org/10.1007/978-3-319-24574-4_30

A 3D primary vessel reconstruction framework with serial microscopy images. / Liang, Yanhui; Wang, Fusheng; Treanor, Darren et al.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings. ed. / Alejandro F. Frangi; Nassir Navab; Joachim Hornegger; William M. Wells. Springer Verlag, 2015. p. 251-259 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9351).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A 3D primary vessel reconstruction framework with serial microscopy images

AU - Liang, Yanhui

AU - Wang, Fusheng

AU - Treanor, Darren

AU - Magee, Derek

AU - Teodoro, George

AU - Zhu, Yangyang

AU - Kong, Jun

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscopy images of liver tissue, we identify primary vessels with an improved variational level set framework at each 2D slide. We propose a Vessel Directed Fitting Energy (VDFE) to provide prior information on vessel wall probability in an energy minimization paradigm. We find the optimal vessel cross-section associations along the image sequence with a two-stage procedure. Vessel mappings are first found between each pair of adjacent slides with a similarity function for four association cases. These bi-slide vessel components are further linked by Bayesian Maximum A Posteriori (MAP) estimation where the posterior probability is modeled as a Markov chain. The efficacy of the proposed method is demonstrated with 54 whole slide microscopy images of sequential sections from a human liver.

AB - Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscopy images of liver tissue, we identify primary vessels with an improved variational level set framework at each 2D slide. We propose a Vessel Directed Fitting Energy (VDFE) to provide prior information on vessel wall probability in an energy minimization paradigm. We find the optimal vessel cross-section associations along the image sequence with a two-stage procedure. Vessel mappings are first found between each pair of adjacent slides with a similarity function for four association cases. These bi-slide vessel components are further linked by Bayesian Maximum A Posteriori (MAP) estimation where the posterior probability is modeled as a Markov chain. The efficacy of the proposed method is demonstrated with 54 whole slide microscopy images of sequential sections from a human liver.

UR - https://www.scopus.com/pages/publications/84951820289

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DO - 10.1007/978-3-319-24574-4_30

M3 - Conference contribution

C2 - 26478919

AN - SCOPUS:84951820289

SN - 9783319245737

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 251

EP - 259

BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings

A2 - Frangi, Alejandro F.

A2 - Navab, Nassir

A2 - Hornegger, Joachim

A2 - Wells, William M.

PB - Springer Verlag

T2 - 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015

Y2 - 5 October 2015 through 9 October 2015

ER -

Liang Y, Wang F, Treanor D, Magee D, Teodoro G, Zhu Y et al. A 3D primary vessel reconstruction framework with serial microscopy images. In Frangi AF, Navab N, Hornegger J, Wells WM, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings. Springer Verlag. 2015. p. 251-259. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-24574-4_30

A 3D primary vessel reconstruction framework with serial microscopy images

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