Literature DB >> 19175137

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

Maryellen L Giger1, Heang-Ping Chan, John Boone.   

Abstract

The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists-as opposed to a completely automatic computer interpretation-focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous-from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects-collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more-from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.

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Mesh:

Year:  2008        PMID: 19175137      PMCID: PMC2673617          DOI: 10.1118/1.3013555

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  340 in total

1.  A pattern classification approach to characterizing solitary pulmonary nodules imaged on high resolution CT: preliminary results.

Authors:  M F McNitt-Gray; E M Hart; N Wyckoff; J W Sayre; J G Goldin; D R Aberle
Journal:  Med Phys       Date:  1999-06       Impact factor: 4.071

2.  Development of an automated method for detecting mammographic masses with a partial loss of region.

Authors:  Y Hatanaka; T Hara; H Fujita; S Kasai; T Endo; T Iwase
Journal:  IEEE Trans Med Imaging       Date:  2001-12       Impact factor: 10.048

3.  Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images.

Authors:  Masahito Aoyama; Qiang Li; Shigehiko Katsuragawa; Heber MacMahon; Kunio Doi
Journal:  Med Phys       Date:  2002-05       Impact factor: 4.071

4.  Computer-assisted detection of mammographic masses: a template matching scheme based on mutual information.

Authors:  Georgia D Tourassi; Rene Vargas-Voracek; David M Catarious; Carey E Floyd
Journal:  Med Phys       Date:  2003-08       Impact factor: 4.071

5.  A fully automated system for screening xeromammograms.

Authors:  J L Semmlow; A Shadagopappan; L V Ackerman; W Hand; F S Alcorn
Journal:  Comput Biomed Res       Date:  1980-08

6.  Factors influencing quantitative CT measurements of solitary pulmonary nodules.

Authors:  E A Zerhouni; J F Spivey; R H Morgan; F P Leo; F P Stitik; S S Siegelman
Journal:  J Comput Assist Tomogr       Date:  1982-12       Impact factor: 1.826

7.  Computer-aided diagnosis applied to US of solid breast nodules by using neural networks.

Authors:  D R Chen; R F Chang; Y L Huang
Journal:  Radiology       Date:  1999-11       Impact factor: 11.105

8.  CT colonography: influence of 3D viewing and polyp candidate features on interpretation with computer-aided detection.

Authors:  Rong Shi; Pamela Schraedley-Desmond; Sandy Napel; Eric W Olcott; R Brooke Jeffrey; Judy Yee; Michael E Zalis; Daniel Margolis; David S Paik; Anthony J Sherbondy; Padmavathi Sundaram; Christopher F Beaulieu
Journal:  Radiology       Date:  2006-06       Impact factor: 11.105

9.  Computerized detection and classification of cancer on breast ultrasound.

Authors:  Karen Drukker; Maryellen L Giger; Carl J Vyborny; Ellen B Mendelson
Journal:  Acad Radiol       Date:  2004-05       Impact factor: 3.173

10.  Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection: pilot clinical trial.

Authors:  Mark A Helvie; Lubomir Hadjiiski; Erini Makariou; Heang-Ping Chan; Nicholas Petrick; Berkman Sahiner; Shih-Chung B Lo; Matthew Freedman; Dorit Adler; Janet Bailey; Caroline Blane; Donna Hoff; Karen Hunt; Lynn Joynt; Katherine Klein; Chintana Paramagul; Stephanie K Patterson; Marilyn A Roubidoux
Journal:  Radiology       Date:  2004-02-27       Impact factor: 11.105

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  76 in total

1.  Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection images.

Authors:  Ravi K Samala; Heang-Ping Chan; Yao Lu; Lubomir M Hadjiiski; Jun Wei; Mark A Helvie
Journal:  Phys Med Biol       Date:  2014-11-13       Impact factor: 3.609

2.  Special Section Guest Editorial:Radiomics and Imaging Genomics: Quantitative Imaging for Precision Medicine.

Authors:  Sandy Napel; Maryellen Giger
Journal:  J Med Imaging (Bellingham)       Date:  2015-12-11

3.  Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions.

Authors:  Neha Bhooshan; Maryellen Giger; Milica Medved; Hui Li; Abbie Wood; Yading Yuan; Li Lan; Angelica Marquez; Greg Karczmar; Gillian Newstead
Journal:  J Magn Reson Imaging       Date:  2013-09-10       Impact factor: 4.813

4.  Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE.

Authors:  Andrew R Jamieson; Maryellen L Giger; Karen Drukker; Hui Li; Yading Yuan; Neha Bhooshan
Journal:  Med Phys       Date:  2010-01       Impact factor: 4.071

5.  Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.

Authors:  Mitsutaka Nemoto; Naoto Hayashi; Shouhei Hanaoka; Yukihiro Nomura; Soichiro Miki; Takeharu Yoshikawa
Journal:  J Digit Imaging       Date:  2017-10       Impact factor: 4.056

6.  Enhancement of breast CADx with unlabeled data.

Authors:  Andrew R Jamieson; Maryellen L Giger; Karen Drukker; Lorenzo L Pesce
Journal:  Med Phys       Date:  2010-08       Impact factor: 4.071

7.  Quality assurance and training procedures for computer-aided detection and diagnosis systems in clinical use.

Authors:  Zhimin Huo; Ronald M Summers; Sophie Paquerault; Joseph Lo; Jeffrey Hoffmeister; Samuel G Armato; Matthew T Freedman; Jesse Lin; Shih-Chung Ben Lo; Nicholas Petrick; Berkman Sahiner; David Fryd; Hiroyuki Yoshida; Heang-Ping Chan
Journal:  Med Phys       Date:  2013-07       Impact factor: 4.071

8.  Investigating the link between radiologists' gaze, diagnostic decision, and image content.

Authors:  Georgia Tourassi; Sophie Voisin; Vincent Paquit; Elizabeth Krupinski
Journal:  J Am Med Inform Assoc       Date:  2013-06-20       Impact factor: 4.497

9.  A review of computer-aided diagnosis in thoracic and colonic imaging.

Authors:  Kenji Suzuki
Journal:  Quant Imaging Med Surg       Date:  2012-09

10.  Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging.

Authors:  Qiyuan Hu; Heather M Whitney; Maryellen L Giger
Journal:  J Med Imaging (Bellingham)       Date:  2020-08-24
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