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Series in Machine Perception and Artificial Intelligence - Vol. 9
STATE OF THE ART IN DIGITAL MAMMOGRAPHIC IMAGE ANALYSIS
edited by K W Bowyer (University of South Florida, USA) & S Astley (University of Manchester, UK)
This book provides a detailed assessment of the state of the art in automated techniques for the analysis of digital mammogram images. Topics covered include a variety of approaches for image processing and pattern recognition aimed at assisting the physician in the task of detecting tumors from evidence in mammogram images. The chapters are written by recognized experts in the field and are revised versions of papers selected from those presented at the "First International Workshop on Mammogram Image Analysis" held in San Jose as part of the 1993 Biomedical Image Processing conference.
Contents:
- Automation in Mammography: Computer Vision and Human Perception (S
Astley et al.)
- Restoration of Mammographic Images in the Presence of Signal-Dependent Noise (F Aghdasi et al.)
- Computer-Aided Detection and Diagnosis of Masses and Clustered Microcalcifications from Digital Mammograms (R M Nishikawa et al.)
- Feature Extraction for Computer-Aided Analysis of Mammograms (H Bårman et al.)
- Detection and Classification of Mammographic Calcifications (L Shen et al.)
- Comparative Evaluation of Pattern Recognition Techniques for Detection of Microcalcifications in Mammography (K S Woods et al.)
- Automated Detection of Breast Asymmetry Using Anatomical Features (P Miller & S Astley)
- Image Processing and Computer Aided Diagnosis in Digital Mammography "A Radiologist's Perspective" (E D Pisano & F Shtern)
- and other papers
Readership: Computer scientists and biomedical engineers.
| 308pp |
Pub. date: Jul 1994 |
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* Special price applies only to individuals purchasing online and cannot be used in conjunction with any other offers.
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