Abstract

application) The goal of the proposed research is to develop, as aids to radiologists, computerized schemes for the detection and classification of pulmonary nodules in digital chest images (including conventional posterior-anterior images, energy-subtracted images and CT images), and masses and parenchymal distortions in digital mammograms. These methods have the potential to increase diagnostic accuracy in the detection of cancer by reducing the """"""""miss-rates"""""""" associated with unaided radiologists' readings. The investigators plan to (1) create a database in order to investigate the distinguishing characteristics of lung nodules and breast masses, (2) develop digital filters for enhancing and suppressing nodules in PA chest images in order to facilitate the removal of normal structured anatomic background, (3) develop feature-extraction techniques for nodules in PA, dual-energy and CT chest images, (4) investigate pattern-recognition techniques for masses and parenchymal distortions in bilateral digital mammograms, (5) develop a method for the classification of breast masses based on the spectral characteristics of spiculations and (6) evaluate the efficacy of the computer-aided schemes compared with unaided radiologists' performance using ROC analysis and FROC analysis.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA048985-03
Application #
3192907
Study Section
Diagnostic Radiology Study Section (RNM)
Project Start
1989-12-01
Project End
1994-11-30
Budget Start
1991-12-01
Budget End
1992-11-30
Support Year
3
Fiscal Year
1992
Total Cost
Indirect Cost

  Institution

Name
University of Chicago
Department
Type
Schools of Medicine
DUNS #
225410919
City
Chicago
State
IL
Country
United States
Zip Code
60637

  Publications

Jiang, Y; Nishikawa, R M; Wolverton, D E et al. (1996) Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology 198:671-8
Caligiuri, P; Giger, M L; Favus, M (1994) Multifractal radiographic analysis of osteoporosis. Med Phys 21:503-8
Armato 3rd, S G; Giger, M L; MacMahon, H (1994) Computerized detection of abnormal asymmetry in digital chest radiographs. Med Phys 21:1761-8
Giger, M L; Bae, K T; MacMahon, H (1994) Computerized detection of pulmonary nodules in computed tomography images. Invest Radiol 29:459-65
Vyborny, C J; Giger, M L (1994) Computer vision and artificial intelligence in mammography. AJR Am J Roentgenol 162:699-708
Nishikawa, R M; Giger, M L; Doi, K et al. (1994) Effect of case selection on the performance of computer-aided detection schemes. Med Phys 21:265-9
Wu, Y C; Doi, K; Giger, M L et al. (1994) Reduction of false positives in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis, and a rule-based scheme. J Digit Imaging 7:196-207
Zhang, W; Doi, K; Giger, M L et al. (1994) Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network. Med Phys 21:517-24
Yin, F F; Giger, M L; Doi, K et al. (1994) Computerized detection of masses in digital mammograms: automated alignment of breast images and its effect on bilateral-subtraction technique. Med Phys 21:445-52
Giger, M L; Vyborny, C J; Schmidt, R A (1994) Computerized characterization of mammographic masses: analysis of spiculation. Cancer Lett 77:201-11

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