Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

被引：121

作者：

Rudyanto, Rina D. ^{[1
]}

Kerkstra, Sjoerd ^{[2
]}

van Rilowort, Eva M. ^{[2
]}

Fetita, Catalin ^{[3
]}

Brillet, Pierre-Yves ^{[3
]}

Lefevre, Christophe ^{[3
]}

Xue, Wenzhe ^{[4
]}

Zhu, Xiangjun ^{[4
]}

Liang, Jianming ^{[4
]}

Oksuz, Ilkay ^{[5
]}

Unay, Devrim ^{[5
]}

Kadipasoglu, Kamuran ^{[5
]}

Estepar, Raul San Jose ^{[6
]}

Ross, James C. ^{[6
]}

Washko, George R. ^{[6
]}

Prieto, Juan-Carlos ^{[7
]}

Hernandez Hoyos, Marcela ^{[8
]}

Orkisz, Maciej ^{[7
]}

Meine, Hans ^{[9
]}

Huellebrand, Markus ^{[9
]}

Stoecker, Christina ^{[9
]}

Mir, Fernando Lopez

Naranjo, Valery

Villanueva, Eliseo

Staring, Marius ^{[10
]}

Xiao, Changyan ^{[11
]}

Stoel, Berend C. ^{[10
]}

Fabijanska, Anna ^{[12
]}

Smistad, Erik ^{[13
]}

Elster, Anne C. ^{[13
]}

Lindseth, Frank ^{[13
]}

Foruzan, Amir Hossein ^{[14
]}

Kiros, Ryan ^{[15
]}

Popuri, Karteek ^{[15
]}

Cobzas, Dana ^{[15
]}

Jimenez-Carretero, Daniel ^{[16
,17
]}

Santos, Andres ^{[16
,17
]}

Ledesma-Carbayo, Maria J. ^{[16
,17
]}

Helmberger, Michael ^{[18
]}

Urschler, Martin ^{[19
]}

Pienn, Michael ^{[20
]}

Bosboom, Dennis G. H. ^{[2
]}

Campo, Arantza ^{[21
]}

Prokop, Mathias ^{[2
]}

de Jong, Pim A. ^{[22
]}

Ortiz-de-Solorzano, Carlos ^{[1
]}

Munoz-Barrutia, Arrate ^{[1
]}

van Ginneken, Bram ^{[2
]}

机构：

[1] Univ Navarra, Ctr Appl Med Res, E-31080 Pamplona, Spain

[2] Radboud Univ Nijmegen, Med Ctr, Diagnost Image Anal Grp, NL-6525 ED Nijmegen, Netherlands

[3] Inst SudParis Telecom, Paris, France

[4] Arizona State Univ, Tempe, AZ 85287 USA

[5] Bahcesehir Univ, Istanbul, Turkey

[6] Brigham & Womens Hosp, Boston, MA 02115 USA

[7] Univ Lyon, CREATIS, Lyon, France

[8] Univ Los Andes, Bogota, Colombia

[9] Fraunhofer MEVIS, Bremen, Germany

[10] Leiden Univ, Med Ctr, Div Image Proc LKEB, NL-2300 RA Leiden, Netherlands

[11] Hunan Univ, Changsha, Hunan, Peoples R China

[12] Lodz Univ Technol, Inst Appl Comp Sci, Lodz, Poland

[13] Norwegian Univ Sci & Technol, Oslo, Norway

[14] Shahed Univ, Tehran, Iran

[15] Univ Alberta, Edmonton, AB T6G 2M7, Canada

[16] Univ Politecn Madrid, E-28040 Madrid, Spain

[17] CIBER BBN, Zaragoza, Spain

[18] Graz Univ Technol, Inst Comp Vis & Graph, A-8010 Graz, Austria

[19] Ludwig Boltzmann Inst Clin Forens Imaging, Graz, Austria

[20] Ludwig Boltzmann Inst Lung Vasc Res, Graz, Austria

[21] Univ Navarra, Univ Navarra Clin, Dept Pulm, E-31080 Pamplona, Spain

[22] Univ Med Ctr, Dept Radiol, Utrecht, Netherlands

来源：

MEDICAL IMAGE ANALYSIS | 2014年 / 18卷 / 07期

关键词：

Thoracic computed tomography; Lung vessels; Algorithm comparison; Segmentation; Challenge; ARTERY-VEIN SEPARATION; CURVILINEAR STRUCTURES; PULMONARY-EMBOLISM; AIDED DETECTION; CT; EXTRACTION; TREE; ENHANCEMENT; FILTER; QUANTIFICATION;

D O I：

10.1016/j.media.2014.07.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：1217 / 1232

页数：16

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