Literature DB >> 20033494

A comparison of ground truth estimation methods.

Alberto M Biancardi1, Artit C Jirapatnakul, Anthony P Reeves.   

Abstract

PURPOSE: Knowledge of the exact shape of a lesion, or ground truth (GT), is necessary for the development of diagnostic tools by means of algorithm validation, measurement metric analysis, accurate size estimation. Four methods that estimate GTs from multiple readers' documentations by considering the spatial location of voxels were compared: thresholded Probability-Map at 0.50 (TPM(0.50)) and at 0.75 (TPM(0.75)), simultaneous truth and performance level estimation (STAPLE) and truth estimate from self distances (TESD).
METHODS: A subset of the publicly available Lung Image Database Consortium archive was used, selecting pulmonary nodules documented by all four radiologists. The pair-wise similarities between the estimated GTs were analyzed by computing the respective Jaccard coefficients. Then, with respect to the readers' marking volumes, the estimated volumes were ranked and the sign test of the differences between them was performed.
RESULTS: (a) the rank variations among the four methods and the volume differences between STAPLE and TESD are not statistically significant, (b) TPM(0.50) estimates are statistically larger (c) TPM(0.75) estimates are statistically smaller (d) there is some spatial disagreement in the estimates as the one-sided 90% confidence intervals between TPM(0.75) and TPM(0.50), TPM(0.75) and STAPLE, TPM(0.75) and TESD, TPM(0.50) and STAPLE, TPM(0.50) and TESD, STAPLE and TESD, respectively, show: [0.67, 1.00], [0.67, 1.00], [0.77, 1.00], [0.93, 1.00], [0.85, 1.00], [0.85, 1.00].
CONCLUSIONS: The method used to estimate the GT is important: the differences highlighted that STAPLE and TESD, notwithstanding a few weaknesses, appear to be equally viable as a GT estimator, while the increased availability of computing power is decreasing the appeal afforded to TPMs. Ultimately, the choice of which GT estimation method, between the two, should be preferred depends on the specific characteristics of the marked data that is used with respect to the two elements that differentiate the method approaches: relative reliabilities of the readers and the reliability of the region boundaries.

Mesh:

Year:  2009        PMID: 20033494     DOI: 10.1007/s11548-009-0401-3

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  14 in total

1.  New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada.

Authors:  P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther
Journal:  J Natl Cancer Inst       Date:  2000-02-02       Impact factor: 13.506

2.  Small pulmonary nodules: volume measurement at chest CT--phantom study.

Authors:  Jane P Ko; Henry Rusinek; Erika L Jacobs; James S Babb; Margrit Betke; Georgeann McGuinness; David P Naidich
Journal:  Radiology       Date:  2003-09       Impact factor: 11.105

3.  Lung image database consortium: developing a resource for the medical imaging research community.

Authors:  Samuel G Armato; Geoffrey McLennan; Michael F McNitt-Gray; Charles R Meyer; David Yankelevitz; Denise R Aberle; Claudia I Henschke; Eric A Hoffman; Ella A Kazerooni; Heber MacMahon; Anthony P Reeves; Barbara Y Croft; Laurence P Clarke
Journal:  Radiology       Date:  2004-09       Impact factor: 11.105

4.  An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision.

Authors:  Yuri Boykov; Vladimir Kolmogorov
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2004-09       Impact factor: 6.226

5.  Robust anisotropic Gaussian fitting for volumetric characterization of pulmonary nodules in multislice CT.

Authors:  Kazunori Okada; Dorin Comaniciu; Arun Krishnan
Journal:  IEEE Trans Med Imaging       Date:  2005-03       Impact factor: 10.048

6.  Evaluation of lung MDCT nodule annotation across radiologists and methods.

Authors:  Charles R Meyer; Timothy D Johnson; Geoffrey McLennan; Denise R Aberle; Ella A Kazerooni; Heber Macmahon; Brian F Mullan; David F Yankelevitz; Edwin J R van Beek; Samuel G Armato; Michael F McNitt-Gray; Anthony P Reeves; David Gur; Claudia I Henschke; Eric A Hoffman; Peyton H Bland; Gary Laderach; Richie Pais; David Qing; Chris Piker; Junfeng Guo; Adam Starkey; Daniel Max; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2006-10       Impact factor: 3.173

7.  The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation.

Authors:  Michael F McNitt-Gray; Samuel G Armato; Charles R Meyer; Anthony P Reeves; Geoffrey McLennan; Richie C Pais; John Freymann; Matthew S Brown; Roger M Engelmann; Peyton H Bland; Gary E Laderach; Chris Piker; Junfeng Guo; Zaid Towfic; David P-Y Qing; David F Yankelevitz; Denise R Aberle; Edwin J R van Beek; Heber MacMahon; Ella A Kazerooni; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-12       Impact factor: 3.173

8.  The Lung Image Database Consortium (LIDC): a comparison of different size metrics for pulmonary nodule measurements.

Authors:  Anthony P Reeves; Alberto M Biancardi; Tatiyana V Apanasovich; Charles R Meyer; Heber MacMahon; Edwin J R van Beek; Ella A Kazerooni; David Yankelevitz; Michael F McNitt-Gray; Geoffrey McLennan; Samuel G Armato; Claudia I Henschke; Denise R Aberle; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-12       Impact factor: 3.173

9.  Shape-based averaging.

Authors:  Torsten Rohlfing; Calvin R Maurer
Journal:  IEEE Trans Image Process       Date:  2007-01       Impact factor: 10.856

10.  Volume determinations using computed tomography.

Authors:  R S Breiman; J W Beck; M Korobkin; R Glenny; O E Akwari; D K Heaston; A V Moore; P C Ram
Journal:  AJR Am J Roentgenol       Date:  1982-02       Impact factor: 3.959

View more
  4 in total

1.  Evaluation of computer-aided detection and diagnosis systems.

Authors:  Nicholas Petrick; Berkman Sahiner; Samuel G Armato; Alberto Bert; Loredana Correale; Silvia Delsanto; Matthew T Freedman; David Fryd; David Gur; Lubomir Hadjiiski; Zhimin Huo; Yulei Jiang; Lia Morra; Sophie Paquerault; Vikas Raykar; Frank Samuelson; Ronald M Summers; Georgia Tourassi; Hiroyuki Yoshida; Bin Zheng; Chuan Zhou; Heang-Ping Chan
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

2.  Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study.

Authors:  M A Deeley; A Chen; R Datteri; J H Noble; A J Cmelak; E F Donnelly; A W Malcolm; L Moretti; J Jaboin; K Niermann; Eddy S Yang; David S Yu; F Yei; T Koyama; G X Ding; B M Dawant
Journal:  Phys Med Biol       Date:  2011-07-01       Impact factor: 3.609

3.  The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.

Authors:  Samuel G Armato; Geoffrey McLennan; Luc Bidaut; Michael F McNitt-Gray; Charles R Meyer; Anthony P Reeves; Binsheng Zhao; Denise R Aberle; Claudia I Henschke; Eric A Hoffman; Ella A Kazerooni; Heber MacMahon; Edwin J R Van Beeke; David Yankelevitz; Alberto M Biancardi; Peyton H Bland; Matthew S Brown; Roger M Engelmann; Gary E Laderach; Daniel Max; Richard C Pais; David P Y Qing; Rachael Y Roberts; Amanda R Smith; Adam Starkey; Poonam Batrah; Philip Caligiuri; Ali Farooqi; Gregory W Gladish; C Matilda Jude; Reginald F Munden; Iva Petkovska; Leslie E Quint; Lawrence H Schwartz; Baskaran Sundaram; Lori E Dodd; Charles Fenimore; David Gur; Nicholas Petrick; John Freymann; Justin Kirby; Brian Hughes; Alessi Vande Casteele; Sangeeta Gupte; Maha Sallamm; Michael D Heath; Michael H Kuhn; Ekta Dharaiya; Richard Burns; David S Fryd; Marcos Salganicoff; Vikram Anand; Uri Shreter; Stephen Vastagh; Barbara Y Croft
Journal:  Med Phys       Date:  2011-02       Impact factor: 4.071

4.  Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions.

Authors:  M A Deeley; A Chen; R D Datteri; J Noble; A Cmelak; E Donnelly; A Malcolm; L Moretti; J Jaboin; K Niermann; Eddy S Yang; David S Yu; B M Dawant
Journal:  Phys Med Biol       Date:  2013-05-17       Impact factor: 3.609

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.