QuPath: Open source software for digital pathology image analysis

被引：4938

作者：

Bankhead, Peter ^{[1
]}

Loughrey, Maurice B. ^{[1
,2
]}

Fernandez, Jose A. ^{[1
]}

Dombrowski, Yvonne ^{[3
]}

Mcart, Darragh G. ^{[1
]}

Dunne, Philip D. ^{[1
]}

McQuaid, Stephen ^{[1
,2
]}

Gray, Ronan T. ^{[4
]}

Murray, Liam J. ^{[4
]}

Coleman, Helen G. ^{[4
]}

James, Jacqueline A. ^{[1
,2
]}

Salto-Tellez, Manuel ^{[1
,2
]}

Hamilton, Peter W. ^{[1
]}

机构：

[1] Queens Univ Belfast, Ctr Canc Res & Cell Biol, Northern Ireland Mol Pathol Lab, Belfast, Antrim, North Ireland

[2] Belfast Hlth & Social Care Trust, Tissue Pathol, Belfast, Antrim, North Ireland

[3] Queens Univ Belfast, Ctr Expt Med, Belfast, Antrim, North Ireland

[4] Queens Univ Belfast, Canc Epidemiol & Hlth Serv Res Grp, Ctr Publ Hlth, Belfast, Antrim, North Ireland

来源：

SCIENTIFIC REPORTS | 2017年 / 7卷

关键词：

PATTERNS; PLATFORM; CANCER;

D O I：

10.1038/s41598-017-17204-5

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath's flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.

引用

页数：7

共 34 条

[1] SLIC Superpixels Compared to State-of-the-Art Superpixel Methods [J].

Achanta, Radhakrishna ;

Shaji, Appu ;

Smith, Kevin ;

Lucchi, Aurelien ;

Fua, Pascal ;

Suesstrunk, Sabine .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (11) :2274-2281

[2] Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration [J].

Altman, Douglas G. ;

McShane, Lisa M. ;

Sauerbrei, Willi ;

Taube, Sheila E. .

PLOS MEDICINE, 2012, 9 (05)

[3]

[Anonymous], 2016, A Language and Environment for Statistical Computing

[4] The prognostic significance of the aberrant extremes of p53 immunophenotypes in breast cancer [J].

Boyle, David P. ;

McArt, Darragh G. ;

Irwin, Gareth ;

Wilhelm-Benartzi, Charlotte S. ;

Lioe, Tong F. ;

Sebastian, Elena ;

McQuaid, Stephen ;

Hamilton, Peter W. ;

James, Jacqueline A. ;

Mullan, Paul B. ;

Catherwood, Mark A. ;

Harkin, D. Paul ;

Salto-Tellez, Manuel .

HISTOPATHOLOGY, 2014, 65 (03) :340-352

[5] Random forests [J].

Breiman, L .

MACHINE LEARNING, 2001, 45 (01) :5-32

[6] A call for bioimaging software usability [J].

Carpenter, Anne E. ;

Kamentsky, Lee ;

Eliceiri, Kevin W. .

NATURE METHODS, 2012, 9 (07) :666-670

[7]

de Chaumont F, 2012, NAT METHODS, V9, P690, DOI [10.1038/NMETH.2075, 10.1038/nmeth.2075]

[8] Analyzing huge pathology images with open source software [J].

Deroulers, Christophe ;

Ameisen, David ;

Badoual, Mathilde ;

Gerin, Chloe ;

Granier, Alexandre ;

Lartaud, Marc .

DIAGNOSTIC PATHOLOGY, 2013, 8

[9]

Dunne P. D., 2016, CANC IMMUNOL RES, P1

[10] Type, density, and location of immune cells within human colorectal tumors predict clinical outcome [J].

Galon, Jerom ;

Costes, Anne ;

Sanchez-Cabo, Fatima ;

Kirilovsky, Amos ;

Mlecnik, Bernhard ;

Lagorce-Pages, Christine ;

Tosolini, Marie ;

Camus, Matthieu ;

Berger, Anne ;

Wind, Philippe ;

Zinzindohoue, Franck ;

Bruneval, Patrick ;

Cugnenc, Paul-Henri ;

Trajanoski, Zlatko ;

Fridman, Wolf-Herman ;

Pages, Franck .

SCIENCE, 2006, 313 (5795) :1960-1964

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