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The Lung Image Database Consortium (LIDC):

The Lung Image Database Consortium (LIDC):. Fundamental Issues for the Creation of a Resource for the Image Processing Research Community. Exhibit Learning Objectives:. Learn about the LIDC’s goals and methods for creating: a publicly available database,

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The Lung Image Database Consortium (LIDC):

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  1. The Lung Image Database Consortium (LIDC): Fundamental Issues for the Creation of a Resource for the Image Processing Research Community LIDC Education Exhibit - RSNA 2003

  2. Exhibit Learning Objectives: • Learn about the LIDC’s goals and methods for creating: a publicly available database, for the development, training, and evaluation of Computer-Aided Diagnosis (CAD) methods, for lung cancer detection and diagnosis using helical CT. LIDC Education Exhibit - RSNA 2003

  3. Learning Objectives: • Learn about challenges in interpreting CT image data sets for the detection and diagnosis of lung cancer LIDC Education Exhibit - RSNA 2003

  4. Learning Objectives: • Learn about the intricacies of establishing spatial “truth” for lesion location and boundary. LIDC Education Exhibit - RSNA 2003

  5. The Challenge: Lung Cancer • Cancer of the lung and bronchus is the leading fatal malignancy in the United States. • Five-year survival is low, but treatment of early-stage disease improves chances of survival considerably. LIDC Education Exhibit - RSNA 2003

  6. The Challenge: Lung Cancer • Given: • Promising results from recent studies involving the use of helical computed tomography (CT) for the early detection of lung cancer • As well as rapid developments in Multi-detector CT (MDCT) technology which provide for the possibility of the detection of smaller lung nodules and offers a potentially effective tool for earlier detection. • There has been an increased interest in computer-aided diagnosis (CAD) techniques applied to CT imaging for lung cancer to assist radiologists’ with their decision-making. LIDC Education Exhibit - RSNA 2003

  7. The NCI Response: Forming the LIDC To stimulate research in the area of CAD, the National Cancer Institute (NCI) formed a consortium of institutions to develop the standards and consensus necessary for constructing an image database resource of thoracic helical CT images. LIDC Education Exhibit - RSNA 2003

  8. Motivation • The development of CAD methods by the imaging research community would be facilitated and enhanced through access to a repository of CT image data LIDC Education Exhibit - RSNA 2003

  9. Motivation • The development of CAD methods by the imaging research community would be facilitated and enhanced through access to a repository of CT image data • (1) It would provide data to researchers without access to clinical images LIDC Education Exhibit - RSNA 2003

  10. Motivation • The development of CAD methods by the imaging research community would be facilitated and enhanced through access to a repository of CT image data • (1) It would provide data to researchers without access to clinical images • (2) It would also allow for meaningful comparisons of different CAD methods LIDC Education Exhibit - RSNA 2003

  11. The LIDC This consortium - called the Lung Image Database Consortium (LIDC) - seeks to establish standard formats and processes by which to manage lung images and the related technical and clinical data that will be used by researchers to develop, train and evaluate CAD algorithms for lung cancer detection and diagnosis. LIDC Education Exhibit - RSNA 2003

  12. Member Institutions • Five institutions were selected to form the Lung Image Database Consortium (LIDC) LIDC Education Exhibit - RSNA 2003

  13. Member Institutions Cornell University UCLA University of Chicago University of Iowa University of Michigan LIDC Education Exhibit - RSNA 2003

  14. Steering Committee Cornell University David Yankelevitz Anthony P. Reeves UCLA Michael F. McNitt-Gray Denise R. Aberle University of Chicago Samuel G. Armato III Heber MacMahon University of Iowa Geoffrey McLennan Eric A. Hoffman University of Michigan Charles R. Meyer Ella Kazerooni NCI Laurence P. Clarke Barbara Y. Croft LIDC Education Exhibit - RSNA 2003

  15. Contributing Participants Claudia Henschke, Cornell David Gur, U. of Pittsburgh Robert Wagner, FDA Nicholas Petrick, FDA Lori Dodd, NCI Ed Staab, NCI Daniel Sullivan, NCI Houston Baker, NCI Carey Floyd, Duke Aliya Husain, U. of Chicago Matthew Brown, UCLA Christopher Piker, U. of Iowa Peyton Bland, U. of Michigan Andinet Asmamaw, Cornell Richie Pais, UCLA Antoni Chan, Cornell Gary Laderach, U. of Michigan Junfeng Guo, U. of Iowa Charles Metz, U. of Chicago Roger Engelmann, U. of Chicago Adam Starkey, U. of Chicago Jim Sayre, UCLA Mike Fishbein, UCLA Andy Flint, U. of Michigan Barry DeYoung, U. of Iowa Brian Mullan, U. of Iowa Madeline Vazquez, Cornell LIDC Education Exhibit - RSNA 2003

  16. Mission The mission of the LIDC is the sharing of lung images, especially low-dose helical CT scans of adults screened for lung cancer, and related technical and clinical data for the development and testing of computer-aided detection and diagnosis technology LIDC Education Exhibit - RSNA 2003

  17. Principal Goals To establish standard formats and processes for managing thoracic CT scans and related technical and clinical data for use in the development and testing of computer-aided diagnostic algorithms. LIDC Education Exhibit - RSNA 2003

  18. Principal Goals To establish standard formats and processes for managing thoracic CT scans and related technical and clinical data for use in the development and testing of computer-aided diagnostic algorithms. To develop an image database as a web-accessible international research resource for the development, training, and evaluation of computer-aided diagnostic (CAD) methods for lung cancer detection and diagnosis using helical CT. LIDC Education Exhibit - RSNA 2003

  19. The Database • The database will contain: • a collection of CT scan images • a searchable relational database LIDC Education Exhibit - RSNA 2003

  20. Fundamental Issues for the LIDC LIDC Education Exhibit - RSNA 2003

  21. LIDC Challenge #1 - Define a Nodule • Though at first this seems trivial, the LIDC had significant discussion about what to include and what not to include as a nodule • A Nodule is part of a spectrum of focal abnormalities. • This spectrum includes scars, cancers, benign lesions, calcified lesions, etc. LIDC Education Exhibit - RSNA 2003

  22. What is a Nodule? “nodule: any pulmonary or pleural lesion represented in a radiograph by a sharply defined, discrete, nearly circular opacity 2-30 mm in diameter” from the Fleischner Society's Glossary of Terms for Thoracic Radiology (AJR 1984) LIDC Education Exhibit - RSNA 2003

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  24. What is a Nodule? “nodule: round opacity, at least moderately well marginated and no greater than 3 cm in maximum diameter” from the Fleishner Society's Glossary of Terms for CT of the Lungs (Radiology 1996) LIDC Education Exhibit - RSNA 2003

  25. Nodule LIDC Education Exhibit - RSNA 2003

  26. Is this a Nodule? LIDC Education Exhibit - RSNA 2003

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  38. NOTE: This is the slice which was shown earlier LIDC Education Exhibit - RSNA 2003

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  48. Nodules ( ) Focal Abnormalities What is a Nodule? • a spectrum of abnormalities Calcified Nodule Spiculated Nodule Scar LIDC Education Exhibit - RSNA 2003

  49. LIDC Challenge #1 - Define a Nodule • LIDC Response is to develop a Nodule Visual Library using: • Cases that ARE in Nodule portion of spectrum • Cases that are OUTSIDE Nodule portion of spectrum • Classification by Thoracic Radiologists • In Development Now • Expected Completion Feb 2004. LIDC Education Exhibit - RSNA 2003

  50. Truth Assessment • Investigators will require “truth” information LIDC Education Exhibit - RSNA 2003

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