Literature DB >> 11345275

National Cancer Institute initiative: Lung image database resource for imaging research.

L P Clarke1, B Y Croft, E Staab, H Baker, D C Sullivan.   

Abstract

Preliminary clinical studies suggest that spiral computed tomography (CT) of the lungs can improve early detection of lung cancer in high-risk individuals. More clinical studies are needed, however, before public health recommendations can be proposed for population-based screening. Spiral CT generates large-volume data sets and thus poses problems in terms of implementation of efficient and cost-effective screening methods. Image processing algorithms such as computer assisted diagnostic (CAD) methods have the potential to assist in lesion (eg, nodule) detection on spiral CT studies. CAD methods may also be used to characterize nodules by either assessing the stability or change in size of lesions based on evaluation of serial CT studies, or quantitatively measuring the temporal parameters related to contrast dynamics when using contrast material-enhanced CT studies. CAD methods therefore have the potential to enhance the sensitivity and specificity of spiral CT lung screening studies. Lung cancer screening studies now under investigation create an opportunity to develop an image database that will allow comparison and optimization of CAD algorithms. This database could serve as an important national resource for the academic and industrial research community that is currently involved in the development of CAD methods. The National Cancer Institute request for applications (RFA) (CA-01-001) has already been announced (April 2000) to establish and support a consortium of academic centers to develop this database, the consortium to be referred to as the Lung Image Database Consortium (LIDC). This RFA is now closed. Five academic sites have been selected to be members of the LIDC, the first meeting of this consortium is planned for spring of 2001, and a public meeting is to be held in 2002. This report is abstracted from the previously published RFA to serve as an example of how an initiative is developed by the National Cancer Institute to support a research resource. For specific details of the RFA, please access the following Internet site: http://www. nci.nih.gov/bip/NCI-DIPinisumm.htm#a11.

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Year:  2001        PMID: 11345275     DOI: 10.1016/S1076-6332(03)80555-X

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  11 in total

1.  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

2.  The Lung Image Database Consortium (LIDC): ensuring the integrity of expert-defined "truth".

Authors:  Samuel G Armato; Rachael Y Roberts; Michael F McNitt-Gray; Charles R Meyer; Anthony P Reeves; Geoffrey McLennan; Roger M Engelmann; Peyton H Bland; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-12       Impact factor: 3.173

3.  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

4.  The Lung Image Database Consortium (LIDC): an evaluation of radiologist variability in the identification of lung nodules on CT scans.

Authors:  Samuel G Armato; Michael F McNitt-Gray; Anthony P Reeves; Charles R Meyer; Geoffrey McLennan; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Eric A Hoffman; Claudia I Henschke; Rachael Y Roberts; Matthew S Brown; Roger M Engelmann; Richard C Pais; Christopher W Piker; David Qing; Masha Kocherginsky; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-11       Impact factor: 3.173

Review 5.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

6.  Giving raw data a chance to talk: a demonstration of exploratory visual analytics with a pediatric research database using Microsoft Live Labs Pivot to promote cohort discovery, research, and quality assessment.

Authors:  Teeradache Viangteeravat; Naga Satya V Rao Nagisetty
Journal:  Perspect Health Inf Manag       Date:  2014-01-01

7.  Computed tomography assessment of response to therapy: tumor volume change measurement, truth data, and error.

Authors:  Michael F McNitt-Gray; Luc M Bidaut; Samuel G Armato; Charles R Meyer; Marios A Gavrielides; Charles Fenimore; Geoffrey McLennan; Nicholas Petrick; Binsheng Zhao; Anthony P Reeves; Reinhard Beichel; Hyun-Jung Grace Kim; Lisa Kinnard
Journal:  Transl Oncol       Date:  2009-12       Impact factor: 4.243

8.  Assessment of radiologist performance in the detection of lung nodules: dependence on the definition of "truth".

Authors:  Samuel G Armato; Rachael Y Roberts; Masha Kocherginsky; Denise R Aberle; Ella A Kazerooni; Heber Macmahon; Edwin J R van Beek; David Yankelevitz; Geoffrey McLennan; Michael F McNitt-Gray; Charles R Meyer; Anthony P Reeves; Philip Caligiuri; Leslie E Quint; Baskaran Sundaram; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2009-01       Impact factor: 3.173

9.  The Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) project: a resource for the development of change-analysis software.

Authors:  S G Armato; C R Meyer; M F Mcnitt-Gray; G McLennan; A P Reeves; B Y Croft; L P Clarke
Journal:  Clin Pharmacol Ther       Date:  2008-10       Impact factor: 6.875

10.  A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study.

Authors:  Jayashree Kalpathy-Cramer; Binsheng Zhao; Dmitry Goldgof; Yuhua Gu; Xingwei Wang; Hao Yang; Yongqiang Tan; Robert Gillies; Sandy Napel
Journal:  J Digit Imaging       Date:  2016-08       Impact factor: 4.056

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