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European Radiology
Article
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Radboud Repository
Article . 1997
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Article . 1997
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European Radiology
Article . 1997 . Peer-reviewed
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Computer-assisted reading of mammograms

Authors: Karssemeijer, N.; Hendriks, J.H.C.L.;

Computer-assisted reading of mammograms

Abstract

Techniques developed in computer vision and automated pattern recognition can be applied to assist radiologists in reading mammograms. With the introduction of direct digital mammography this will become a feasible approach. A radiologist in breast cancer screening can use findings of the computer as a second opinion, or as a pointer to suspicious regions. This may increase the sensitivity and specificity of screening programs, and it may avoid the need for double reading. In this paper methods which have been developed for automated detection of mammographic abnormalities are reviewed. Programs for detecting microcalcification clusters and stellate lesions have reached a level of performance which makes application in practice viable. Current programs for recognition of masses and asymmetry perform less well. Large-scale studies still have to demonstrate if radiologists in a screening situation can deal with the relatively large number of false positives which are marked by computer programs, where the number of normal cases is much higher than in observer experiments conducted thus far.

Country
Netherlands
Related Organizations
Keywords

Data Collection and Data Estimation Methodology; Computer Programs, Respiratory System, Respiratory Tract Diseases, Urologic and Male Genital Diseases (Non MeSH), Teaching of Economics, Cardiovascular System, Nervous System, Physiology, General (Non MeSH), Environment and Public Health (Non MeSH), Biomedische Magnetische Resonantie, Neoplasms, Diagnosis, Mass Screening, Musculoskeletal Diseases, Neonatal Diseases and Abnormalities (Non MeSH), Musculoskeletal System, Portfolio Choice, Brain Mapping, Phantoms, Imaging, Stomatognathic Diseases, Calcinosis, General Aggregative Models, Hypothesis Testing, Biological Sciences, Biomedical Magnetic Resonance, Radiographic Image Enhancement, Otorhinolaryngologic Diseases, Cardiovascular Diseases, Health Occupations, Virus Diseases, Female Genital Diseases and Pregnancy Complications (Non MeSH), Mathematical Methods and Programming, Models with Panel Data, Female, Nutritional and Metabolic Diseases (Non MeSH), General Financial Markets, Mammography, Tomography Scanners, X-Ray Computed, Design of Experiments, Endocrine Diseases, Semiparametric and Nonparametric Methods, Digestive System Diseases, Fluids and Secretions (Non MeSH), Urogenital System, Biochemical Phenomena, Metabolism, Nutrition (Non MeSH), Breast Neoplasms, Circulatory, Respiratory Physiology (Non MeSH), Econometric Methods: Single Equation Models, Therapeutics, Symptoms and General Pathology (Non MeSH), Sensitivity and Specificity, Endocrine System (Non MeSH), Econometric and Statistical Methods: Special Topics, Image Interpretation, Computer-Assisted, Animals, Humans, X-Ray Intensifying Screens, General, Technology, Radiologic, Body Regions (Non MeSH), Consumption, Saving, Production, Employment, and Investment, Tissue Types (Non MeSH), General Economics, Musculoskeletal, Neural, Eye Physiology (Non MeSH), Relation of Economics to Other Disciplines, Financial Institutions and Services, Econometric Modeling, Other, Nervous System Diseases, Digestive System, Estimation, Game Theory and Bargaining Theory, Corporate Finance and Governance

  • BIP!
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    40
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
40
Average
Top 10%
Top 10%
Green
bronze