Digital mammography : proceedings of the 2nd International Workshop on Digital Mammography, York, England, 10-12 July 1994
著者
書誌事項
Digital mammography : proceedings of the 2nd International Workshop on Digital Mammography, York, England, 10-12 July 1994
（International congress series, no. 1069）
Elsevier, 1994
大学図書館所蔵 全8件
注記
Includes index
内容説明・目次
内容説明
The Second International Workshop on which this book is based was the follow-up to the first meeting held in San Jose, California, in 1993. It was attended by 90 delegates from 13 countries, representing almost all of the major intemational research groups working in this area. The meeting provided a forum for all researchers in digital mammography to exchange ideas and discuss current research issues. The main topic addressed was the current state of the art in research into approaches which can offer some assistance to the radiologist in detection and recognition of early signs of the disease.
目次
Owing to space limitations, only a selection of the published papers are listed hereunder Preface. Classification and detection of microcalcifications. Dense feature maps for detection of calcification (W.P. Kegelmeyer, jr., M.C. Allmen). Three-dimensional reconstruction of microcalcification clusters within excised breast lesions (S.P. Bates et al). Detection of microcalcifications using wavelets (R.N. Strickland, H.I. Hahn). Use of multiple images/Wavelets. A framework for contrast enhancement by dyadic wavelet analysis (A. Laine, J. Fan, S. Schuler). Registering time sequences of mammograms using two-dimentional image unwarping technique(M.Sallam, K.W. Bowyer) Mammogram analysis by comparison with previous screenings (D. Brzakovic et al.). image acquisition and transmission. Developments in digital mammography with monochromatic and narrow energy band X-rays (R. Beccherle et al). Comparison of digital X-ray cameras for stereotactic breast needle biopsy: an observer performance study (E.A Krupinski, H. Roehrig). Classification and detection of masses. Recognition of stellate lesions in digital mammograms (N. Karssemeijer). The detection of abnormalities in mammograms (S.L. Kok, J.M. Brady, L. Tarassenko). Computer detection of lesions missed by mammography (R.A. Schmidt et al.). Image processing and segmentation. Enriching digital mammogram image analysis with a description of the curvilinear structures (N. Cemeaz, M. Brady). Generating ROC curves for artificial neural networks (K. S. Woods, K.W. Bowyer). A novel approach to aligning mammograms (E.A. Stamatakis et al). Image databases. A training and assessment package for digital mammography (H.J. Sumsion, G.J.S. Parkin, A.R. Cowen). The application of a computed radiography database to a mammographic reporting environment (H.J. Sumsion et al) Radiologist performance. Prompting as an aid to diagnosis in mammography (I.W. Hutt, S.M. Astley, C.R.M. Boggis). To err human, to compute divine? (C.J. Savage et al). Index of authors.
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