The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans
Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resour...
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| Vydané v: | Medical physics (Lancaster) Ročník 38; číslo 2; s. 915 - 931 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
American Association of Physicists in Medicine
01.02.2011
U.S. Government |
| Predmet: | |
| ISSN: | 0094-2405, 2473-4209, 0094-2405 |
| On-line prístup: | Získať plný text |
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| Abstract | Purpose:
The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.
Methods:
Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“
nodule
≥
3
mm
,” “
nodule
<
3
mm
,” and “non-
nodule
≥
3
mm
”). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.
Results:
The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “
nodule
≥
3
mm
” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.
Conclusions:
The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. |
|---|---|
| AbstractList | The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.
Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.
The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.
The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. Purpose: The development of computer‐aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well‐characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public‐private partnership demonstrates the success of a consortium founded on a consensus‐based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two‐phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded‐read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“nodule≥3mm,” “nodule<3mm,” and “non‐nodule≥3mm”). In the subsequent unblinded‐read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “nodule≥3mm” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.PURPOSEThe development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.METHODSSeven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.RESULTSThe Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.CONCLUSIONSThe LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC∕IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“nodule≥3 mm,” “nodule<3 mm,” and “non-nodule≥3 mm”). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “nodule≥3 mm” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC∕IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“ nodule ≥ 3 mm ,” “ nodule < 3 mm ,” and “non- nodule ≥ 3 mm ”). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “ nodule ≥ 3 mm ” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule{>=}3 mm,'''nodule<3 mm,'' and ''non-nodule{>=}3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule{>=}3 mm'' by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice. |
| Author | Starkey, Adam Munden, Reginald F. Jude, C. Matilda Gladish, Gregory W. Clarke, Laurence P. Quint, Leslie E. Freymann, John Burns, Richard Smith, Amanda R. Salganicoff, Marcos Roberts, Rachael Y. Shreter, Uri Dodd, Lori E. Fenimore, Charles Engelmann, Roger M. Hoffman, Eric A. Heath, Michael D. Max, Daniel Sundaram, Baskaran Kuhn, Michael H. Gur, David Dharaiya, Ekta Bland, Peyton H. Brown, Matthew S. Kazerooni, Ella A. Biancardi, Alberto M. McNitt-Gray, Michael F. Zhao, Binsheng Gupte, Sangeeta Meyer, Charles R. Kirby, Justin Anand, Vikram Yankelevitz, David McLennan, Geoffrey Caligiuri, Philip Bidaut, Luc Vastagh, Stephen Sallam, Maha Petrick, Nicholas van Beek, Edwin J. R. Petkovska, Iva Schwartz, Lawrence H. Aberle, Denise R. Reeves, Anthony P. Qing, David P.-Y. Fryd, David S. Armato, Samuel G. Batra, Poonam Laderach, Gary E. Hughes, Brian MacMahon, Heber Pais, Richard C. Farooqi, Ali Henschke, Claudia I. Croft, Barbara Y. Vande Casteele, Alessi |
| Author_xml | – sequence: 1 givenname: Samuel G. surname: Armato fullname: Armato, Samuel G. email: s-armato@uchicago.edu organization: Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637 – sequence: 2 givenname: Geoffrey surname: McLennan fullname: McLennan, Geoffrey organization: Department of Internal Medicine, Pulmonary Division, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, Iowa 52242 – sequence: 3 givenname: Luc surname: Bidaut fullname: Bidaut, Luc organization: University of Texas, MD Anderson Cancer Center, Houston, Texas 77030 – sequence: 4 givenname: Michael F. surname: McNitt-Gray fullname: McNitt-Gray, Michael F. organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 5 givenname: Charles R. surname: Meyer fullname: Meyer, Charles R. organization: Department of Radiology, University of Michigan Medical School, 109 Zina Pitcher Place, A522, Ann Arbor, Michigan 48109 – sequence: 6 givenname: Anthony P. surname: Reeves fullname: Reeves, Anthony P. organization: School of Electrical and Computer Engineering, Cornell University, 392 Rhodes Hall, Ithaca, New York 14853 – sequence: 7 givenname: Binsheng surname: Zhao fullname: Zhao, Binsheng organization: Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, New York 10065 – sequence: 8 givenname: Denise R. surname: Aberle fullname: Aberle, Denise R. organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 9 givenname: Claudia I. surname: Henschke fullname: Henschke, Claudia I. organization: Department of Radiology, Mount Sinai School of Medicine, 1 Gustave Levy Place, New York, New York 10029 – sequence: 10 givenname: Eric A. surname: Hoffman fullname: Hoffman, Eric A. organization: Department of Radiology, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, Iowa 52242 – sequence: 11 givenname: Ella A. surname: Kazerooni fullname: Kazerooni, Ella A. organization: Department of Radiology, University of Michigan Health System, Cardiovascular Center Number 5482, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109 – sequence: 12 givenname: Heber surname: MacMahon fullname: MacMahon, Heber organization: Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637 – sequence: 13 givenname: Edwin J. R. surname: van Beek fullname: van Beek, Edwin J. R. organization: Department of Radiology, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, Iowa 52242 – sequence: 14 givenname: David surname: Yankelevitz fullname: Yankelevitz, David organization: Department of Radiology, Mount Sinai School of Medicine, 1 Gustave Levy Place, New York, New York 10029 – sequence: 15 givenname: Alberto M. surname: Biancardi fullname: Biancardi, Alberto M. organization: School of Electrical and Computer Engineering, Cornell University, 392 Rhodes Hall, Ithaca, New York 14853 – sequence: 16 givenname: Peyton H. surname: Bland fullname: Bland, Peyton H. organization: Department of Radiology, University of Michigan, A502 BSRB, 109 Zina Pitcher Place, Ann Arbor, Michigan 48109 – sequence: 17 givenname: Matthew S. surname: Brown fullname: Brown, Matthew S. organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 18 givenname: Roger M. surname: Engelmann fullname: Engelmann, Roger M. organization: Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637 – sequence: 19 givenname: Gary E. surname: Laderach fullname: Laderach, Gary E. organization: Department of Radiology, University of Michigan, A502 BSRB, 109 Zina Pitcher Place, Ann Arbor, Michigan 48109 – sequence: 20 givenname: Daniel surname: Max fullname: Max, Daniel organization: Department of Radiology, Mount Sinai School of Medicine, 1 Gustave Levy Place, New York, New York 10029 – sequence: 21 givenname: Richard C. surname: Pais fullname: Pais, Richard C. organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 22 givenname: David P.-Y. surname: Qing fullname: Qing, David P.-Y. organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 23 givenname: Rachael Y. surname: Roberts fullname: Roberts, Rachael Y. organization: Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637 – sequence: 24 givenname: Amanda R. surname: Smith fullname: Smith, Amanda R. organization: Department of Radiology, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, Iowa 52242 – sequence: 25 givenname: Adam surname: Starkey fullname: Starkey, Adam organization: Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637 – sequence: 26 givenname: Poonam surname: Batra fullname: Batra, Poonam organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 27 givenname: Philip surname: Caligiuri fullname: Caligiuri, Philip organization: Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637 – sequence: 28 givenname: Ali surname: Farooqi fullname: Farooqi, Ali organization: Department of Radiology, Mount Sinai School of Medicine, 1 Gustave Levy Place, New York, New York 10029 – sequence: 29 givenname: Gregory W. surname: Gladish fullname: Gladish, Gregory W. organization: Department of Diagnostic Radiology, MD Anderson Cancer Center, Unit 1478, 1515 Holcombe Boulevard, Houston, Texas 77030 – sequence: 30 givenname: C. Matilda surname: Jude fullname: Jude, C. Matilda organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 31 givenname: Reginald F. surname: Munden fullname: Munden, Reginald F. organization: Department of Diagnostic Imaging, MD Anderson Cancer Center, Unit 1478, 1515 Holcombe Boulevard, Houston, Texas 77030 – sequence: 32 givenname: Iva surname: Petkovska fullname: Petkovska, Iva organization: Department of Radiological Sciences, David Geffen School of Medicine at UCLA, 924 Westwood Boulevard, Los Angeles, California 90024 – sequence: 33 givenname: Leslie E. surname: Quint fullname: Quint, Leslie E. organization: Department of Radiology, University of Michigan Health Systems, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109 – sequence: 34 givenname: Lawrence H. surname: Schwartz fullname: Schwartz, Lawrence H. organization: Department of Radiology, Box 29, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, New York 10065 – sequence: 35 givenname: Baskaran surname: Sundaram fullname: Sundaram, Baskaran organization: Department of Radiology, University of Michigan Health Systems, CVC 5481, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109 – sequence: 36 givenname: Lori E. surname: Dodd fullname: Dodd, Lori E. organization: National Cancer Institute, 6130 Executive Boulevard, Bethesda, Maryland 20892 – sequence: 37 givenname: Charles surname: Fenimore fullname: Fenimore, Charles organization: Information Access Division, National Institute of Standards and Technology, MS 8940, 100 Bureau Drive, Gaithersburg, Maryland 20899 – sequence: 38 givenname: David surname: Gur fullname: Gur, David organization: Department of Radiology, University of Pittsburgh, 3632 Fifth Avenue, Pittsburgh, Pennsylvania 15213 – sequence: 39 givenname: Nicholas surname: Petrick fullname: Petrick, Nicholas organization: United States Food and Drug Administration, WO62–4118, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993 – sequence: 40 givenname: John surname: Freymann fullname: Freymann, John organization: SAIC-Frederick, Inc., 6130 Executive Boulevard, Bethesda, Maryland 20892 – sequence: 41 givenname: Justin surname: Kirby fullname: Kirby, Justin organization: SAIC-Frederick, Inc., 6130 Executive Boulevard, Bethesda, Maryland 20892 – sequence: 42 givenname: Brian surname: Hughes fullname: Hughes, Brian organization: TerpSys, 2115 East Jefferson Street, Suite 6000, Rockville, Maryland 20852 – sequence: 43 givenname: Alessi surname: Vande Casteele fullname: Vande Casteele, Alessi organization: Agfa HealthCare NV, Septestraat 27, 2640 Mortsel, Belgium – sequence: 44 givenname: Sangeeta surname: Gupte fullname: Gupte, Sangeeta organization: FUJIFILM Medical Systems USA, Inc., 419 West Avenue, Stamford, Connecticut 06902 – sequence: 45 givenname: Maha surname: Sallam fullname: Sallam, Maha organization: iCAD, Inc., Global Headquarters, 98 Spit Brook Road, Suite 100, Nashua, New Hampshire 03062 – sequence: 46 givenname: Michael D. surname: Heath fullname: Heath, Michael D. organization: Carestream Health Inc., 1049 Ridge Road West, Rochester, New York 14615 – sequence: 47 givenname: Michael H. surname: Kuhn fullname: Kuhn, Michael H. organization: Philips Medical Systems DMC GmbH, Roentgenstrasse 24, D-22315 Hamburg, Germany – sequence: 48 givenname: Ekta surname: Dharaiya fullname: Dharaiya, Ekta organization: Philips Healthcare, 595 Miner Road, Highland Heights, Ohio 44143 – sequence: 49 givenname: Richard surname: Burns fullname: Burns, Richard organization: Riverain Medical, 3020 South Tech Boulevard, Miamisburg, Ohio 45342 – sequence: 50 givenname: David S. surname: Fryd fullname: Fryd, David S. organization: Riverain Medical, 3020 South Tech Boulevard, Miamisburg, Ohio 45342 – sequence: 51 givenname: Marcos surname: Salganicoff fullname: Salganicoff, Marcos organization: Siemens Medical Solutions USA, Inc., 51 Valley Stream Parkway, Malvern, Pennsylvania 19355 – sequence: 52 givenname: Vikram surname: Anand fullname: Anand, Vikram organization: Siemens Medical Solutions USA, Inc., 51 Valley Stream Parkway, Malvern, Pennsylvania 19355 – sequence: 53 givenname: Uri surname: Shreter fullname: Shreter, Uri organization: GE Healthcare, 3000 North Grandview Boulevard, W1120, Waukesha, Wisconsin 53188 – sequence: 54 givenname: Stephen surname: Vastagh fullname: Vastagh, Stephen organization: Medical Imaging and Technology Alliance (MITA), 1300 North 17th Street, Suite 1752, Arlington, Virginia 22209 – sequence: 55 givenname: Barbara Y. surname: Croft fullname: Croft, Barbara Y. organization: Cancer Imaging Program, National Cancer Institute, 6130 Executive Boulevard, Bethesda, Maryland 20892 – sequence: 56 givenname: Laurence P. surname: Clarke fullname: Clarke, Laurence P. organization: Cancer Imaging Program, National Cancer Institute, 6130 Executive Boulevard, Bethesda, Maryland 20892 |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/21452728$$D View this record in MEDLINE/PubMed https://www.osti.gov/biblio/22096914$$D View this record in Osti.gov |
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| Keywords | thoracic imaging interobserver variability computed tomography (CT) lung nodule computer-aided diagnosis (CAD) |
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| Notes | Present address: University of Dundee–Ninewells Hospital and Medical School, Clinical Research Centre (CRC), James Arrott Drive, Dundee DD1 9SY, Scotland, United Kingdom. s‐armato@uchicago.edu Present address: University of Texas, MD Anderson Cancer Center, Houston, Texas 77030. Present address: National Institute of Allergy and Infectious Diseases, 6700B Rockledge Drive, Bethesda, Maryland 20892. Present address: VuEssence, Inc., Odessa, Florida 33556. Present address: VA Medical Center West Los Angeles, 11301 Wilshire Boulevard, Building 500, Los Angeles, California 90073. Present address: Department of Radiology, Columbia University Medical Center, 710 West 168th Street, NI‐B‐04H, New York, New York 10032. Present address: Department of Radiology, University of Utah, 30 North 1900 East, Room Number 1A71, Salt Lake City, Utah 84132. Author to whom correspondence should be addressed. Fax: 773‐702‐0371; Electronic mail Present address: Department of Internal Medicine, University Medical Center–LSU, Lafayette, Louisiana 70518. Present address: Clinical Research Imaging Centre, Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, United Kingdom. Present address: BIDMC–Beth Israel Deaconess Medical Center, Radiology W CC‐3, 330 Brookline Avenue, Boston, Massachusetts 02215. Present address: Department of Radiology, Columbia University Medical Center–New York Presbyterian Hospital, 180 Fort Washington Avenue, Harkness Pavilion–HP 3‐320, New York, New York 10032. Previous address: Department of Radiology, Weill Cornell Medical College, New York, New York. Present address: ActiViews, Inc., 10936 North Port Washington Road, Suite 134, Mequon, Wisconsin 53092. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Author to whom correspondence should be addressed. Fax: 773-702-0371; Electronic mail: s-armato@uchicago.edu Present address: Department of Radiology, Columbia University Medical Center, 710 West 168th Street, NI-B-04H, New York, New York 10032. Present address: Department of Radiology, Columbia University Medical Center–New York Presbyterian Hospital, 180 Fort Washington Avenue, Harkness Pavilion–HP 3-320, New York, New York 10032. Present address: BIDMC–Beth Israel Deaconess Medical Center, Radiology W CC-3, 330 Brookline Avenue, Boston, Massachusetts 02215. |
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The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated... Purpose: The development of computer‐aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated... The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a... Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated... |
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| SubjectTerms | 60 APPLIED LIFE SCIENCES Cancer CAT SCANNING CLASSIFICATION Computed tomography computed tomography (CT) Computer aided diagnosis Computer software computerised tomography computer‐aided diagnosis (CAD) Databases, Factual DIAGNOSIS Diagnosis, Computer-Assisted diagnostic radiography Digital radiography Humans interobserver variability lung Lung - diagnostic imaging Lung Neoplasms - diagnostic imaging Lung Neoplasms - pathology lung nodule LUNGS medical computing Medical image quality Medical image reconstruction Medical imaging NEOPLASMS Quality Control Radiation Imaging Physics Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Radiologists Reference Standards thoracic imaging Tomography, X-Ray Computed - methods Tomography, X-Ray Computed - standards Tumor Burden VALIDATION visual databases XML |
| Title | The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans |
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