Literature DB >> 11079834

CADMIUM II: acquisition and representation of radiological knowledge for computerized decision support in mammography.

E Alberdi1, P Taylor, R Lee, J Fox, M Sordo, A Todd-Pokropek.   

Abstract

CADMIUM II is a system for the interpretation of mammograms. A novel aspect of the system is that it combines symbolic reasoning with image processing, in contrast with most other approaches, which use only image processing and rely on artificial neural networks (ANNs) to classify mammograms. A problem of ANNs is that the advice they give cannot be traced back to communicable diagnostic inferences. Our approach is to provide advice based on explicit knowledge about the diagnostic process. To this end, we have conducted a knowledge elicitation study which looked at the descriptors used by expert radiologists when making diagnostic decisions about mammograms. The analysis of the radiologists' reports yielded a set of salient diagnostic features. These were used to inform the advice provided by the symbolic decision making component of CADMIUM II.

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Mesh:

Year:  2000        PMID: 11079834      PMCID: PMC2243967     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  7 in total

1.  The development and evaluation of CADMIUM: a prototype system to assist in the interpretation of mammograms.

Authors:  P Taylor; J Fox; A T Pokropek
Journal:  Med Image Anal       Date:  1999-12       Impact factor: 8.545

2.  Reading and decision aids for improved accuracy and standardization of mammographic diagnosis.

Authors:  C J D'Orsi; D J Getty; J A Swets; R M Pickett; S E Seltzer; B J McNeil
Journal:  Radiology       Date:  1992-09       Impact factor: 11.105

3.  Descriptive terms for mammographic abnormalities: observer variation in application. The Northern Region Breast Screening Radiology Audit Group.

Authors:  W Simpson; F Neilson; P J Kelly
Journal:  Clin Radiol       Date:  1996-10       Impact factor: 2.350

4.  A model for integrating image processing into decision aids for diagnostic radiology.

Authors:  P Taylor; J Fox; A Todd-Pokropek
Journal:  Artif Intell Med       Date:  1997-03       Impact factor: 5.326

5.  Artificial neural networks in mammography: application to decision making in the diagnosis of breast cancer.

Authors:  Y Wu; M L Giger; K Doi; C J Vyborny; R A Schmidt; C E Metz
Journal:  Radiology       Date:  1993-04       Impact factor: 11.105

6.  Variability in radiologists' interpretations of mammograms.

Authors:  J G Elmore; C K Wells; C H Lee; D H Howard; A R Feinstein
Journal:  N Engl J Med       Date:  1994-12-01       Impact factor: 91.245

7.  Application of expert systems to mammographic image analysis.

Authors:  H M Cook; M D Fox
Journal:  Am J Physiol Imaging       Date:  1989
  7 in total
  1 in total

1.  Creating and curating a terminology for radiology: ontology modeling and analysis.

Authors:  Daniel L Rubin
Journal:  J Digit Imaging       Date:  2007-09-15       Impact factor: 4.056

  1 in total

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