Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study
Rina D Rudyanto
(1)
,
Sjoerd Kerkstra
(2)
,
Eva M van Rikxoort
(2)
,
Catalin Fetita
(3, 4)
,
Pierre-Yves Brillet
(5)
,
Christophe Lefevre
(4)
,
Wenzhe Xue
(6)
,
Xiangjun Zhu
(6)
,
Jianming Liang
(7, 6)
,
Ilkay Öksüz
(8)
,
Devrim Ünay
(9)
,
Kamuran Kadipaşaoğlu
(10)
,
Raúl San José Estépar
(11)
,
James C Ross
(11)
,
George R Washko
(11)
,
Juan-Carlos Prieto
(12)
,
Marcela Hernández Hoyos
(13)
,
Maciej Orkisz
(14)
,
Hans Meine
(15)
,
Markus Hüllebrand
(15)
,
Christina Stöcker
(15)
,
Fernando Lopez Mir
(16)
,
Valery Naranjo
(16)
,
Eliseo Villanueva
(17)
,
Marius Staring
(18)
,
Changyan Xiao
(19)
,
Berend C Stoel
(18)
,
Anna Fabijanska
(20)
,
Erik Smistad
(21)
,
Anne C Elster
(21)
,
Frank Lindseth
(21)
,
Amir Hossein Foruzan
(22)
,
Ryan Kiros
(23)
,
Karteek Popuri
(23)
,
Dana Cobzas
(23)
,
Daniel Jimenez-Carretero
(24)
,
Andres Santos
(25)
,
Maria J Ledesma-Carbayo
(24)
,
Michael Helmberger
(26)
,
Martin Urschler
(27)
,
Michael Pienn
(28)
,
Dennis G H Bosboom
(2)
,
Arantza Campo
(29)
,
Arrate Muñoz-Barrutia
(1)
,
Mathias Prokop
(2)
,
Pim A de Jong
(30)
,
Carlos Ortiz-De-Solorzano
(1)
,
Bram van Ginneken
(2)
1
CIMA -
Center for Applied Medical Research [Plamplona]
2 Diagnostic Image Analysis Group [Nijmegen]
3 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
4 TSP - ARTEMIS - Département Advanced Research And Techniques For Multidimensional Imaging Systems
5 H&P - Hypoxie et Poumon : pneumopathologies fibrosantes, modulations ventilatoires et circulatoires
6 ASU - Arizona State University [Tempe]
7 Equipe Image - Laboratoire GREYC - UMR6072
8 Electrical and Electronics Engineering [Istanbul]
9 Biomedical Engineering [Istanbul]
10 Bahcesehir University [Istanbul]
11 Brigham and Women's Hospital [Boston]
12 Images et Modèles
13 UNIANDES - Universidad de los Andes [Bogota]
14 MOTIVATE - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales
15 Fraunhofer MEVIS - Fraunhofer Institute for Digital Medicine
16 UPV - Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia
17 Instituto Interuniversitario de Investigacion en Bioingenieria Y Tecnologia Orientada Al Ser Humano
18 Division of image processing [Leiden]
19 Liaoning Technical University [Huludao]
20 Łódź University of Technology
21 NTNU - Norwegian University of Science and Technology [Trondheim]
22 Shahed University [Téhéran]
23 University of Alberta
24 CIBER-BBN - Biomedical Image Technologies, Biomedical Research Center
25 INPA - Instituto Nacional de Pesquisas da Amazônia = National Institute of Amazonian Research
26 ICG - Institute for Computer Graphics and Vision [Graz]
27 LBI-CFI - Ludwig Boltzmann Institute for Clinical Forensic Imaging [Graz]
28 Ludwig Boltzmann Institute for Lung Vascular Research [Graz]
29 Pulmonary Department [Pamplona]
30 Department of Radiology [Utrecht]
2 Diagnostic Image Analysis Group [Nijmegen]
3 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
4 TSP - ARTEMIS - Département Advanced Research And Techniques For Multidimensional Imaging Systems
5 H&P - Hypoxie et Poumon : pneumopathologies fibrosantes, modulations ventilatoires et circulatoires
6 ASU - Arizona State University [Tempe]
7 Equipe Image - Laboratoire GREYC - UMR6072
8 Electrical and Electronics Engineering [Istanbul]
9 Biomedical Engineering [Istanbul]
10 Bahcesehir University [Istanbul]
11 Brigham and Women's Hospital [Boston]
12 Images et Modèles
13 UNIANDES - Universidad de los Andes [Bogota]
14 MOTIVATE - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales
15 Fraunhofer MEVIS - Fraunhofer Institute for Digital Medicine
16 UPV - Universitat Politècnica de València = Universitad Politecnica de Valencia = Polytechnic University of Valencia
17 Instituto Interuniversitario de Investigacion en Bioingenieria Y Tecnologia Orientada Al Ser Humano
18 Division of image processing [Leiden]
19 Liaoning Technical University [Huludao]
20 Łódź University of Technology
21 NTNU - Norwegian University of Science and Technology [Trondheim]
22 Shahed University [Téhéran]
23 University of Alberta
24 CIBER-BBN - Biomedical Image Technologies, Biomedical Research Center
25 INPA - Instituto Nacional de Pesquisas da Amazônia = National Institute of Amazonian Research
26 ICG - Institute for Computer Graphics and Vision [Graz]
27 LBI-CFI - Ludwig Boltzmann Institute for Clinical Forensic Imaging [Graz]
28 Ludwig Boltzmann Institute for Lung Vascular Research [Graz]
29 Pulmonary Department [Pamplona]
30 Department of Radiology [Utrecht]
Catalin Fetita
- Fonction : Auteur
- PersonId : 749685
- IdHAL : catalin-fetita
- ORCID : 0000-0002-6134-2990
Pierre-Yves Brillet
- Fonction : Auteur
- PersonId : 1026772
- ORCID : 0000-0002-2411-5545
Christophe Lefevre
- Fonction : Auteur
- PersonId : 738903
- IdHAL : christophe-lefevre
- ORCID : 0000-0002-2962-3426
- IdRef : 080788920
Maciej Orkisz
- Fonction : Auteur
- PersonId : 19676
- IdHAL : maciej-orkisz
- ORCID : 0000-0003-1709-5766
- IdRef : 070950091
Résumé
The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.