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Mammographic Image Analysis: Computational Imaging and Vision, cartea 14

Autor R. Highnam, J. M. Brady
en Limba Engleză Paperback – 14 oct 2012
Breast cancer is a major health problem in the Western world, where it is the most common cancer among women. Approximately 1 in 12 women will develop breast cancer during the course of their lives. Over the past twenty years there have been a series of major advances in the manage­ ment of women with breast cancer, ranging from novel chemotherapy and radiotherapy treatments to conservative surgery. The next twenty years are likely to see computerized image analysis playing an increasingly important role in patient management. As applications of image analysis go, medical applications are tough in general, and breast cancer image analysis is one of the toughest. There are many reasons for this: highly variable and irregular shapes of the objects of interest, changing imaging conditions, and the densely textured nature of the images. Add to this the increasing need for quantitative informa­ tion, precision, and reliability (very few false positives), and the image pro­ cessing challenge becomes quite daunting, in fact it pushes image analysis techniques right to their limits.
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Specificații

ISBN-13: 9789401059497
ISBN-10: 9401059497
Pagini: 396
Ilustrații: XI, 379 p.
Dimensiuni: 160 x 240 x 21 mm
Greutate: 0.55 kg
Ediția:Softcover reprint of the original 1st ed. 1999
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Computational Imaging and Vision

Locul publicării:Dordrecht, Netherlands

Public țintă

Research

Descriere

Breast cancer is a major health problem in the Western world, where it is the most common cancer among women. Approximately 1 in 12 women will develop breast cancer during the course of their lives. Over the past twenty years there have been a series of major advances in the manage­ ment of women with breast cancer, ranging from novel chemotherapy and radiotherapy treatments to conservative surgery. The next twenty years are likely to see computerized image analysis playing an increasingly important role in patient management. As applications of image analysis go, medical applications are tough in general, and breast cancer image analysis is one of the toughest. There are many reasons for this: highly variable and irregular shapes of the objects of interest, changing imaging conditions, and the densely textured nature of the images. Add to this the increasing need for quantitative informa­ tion, precision, and reliability (very few false positives), and the image pro­ cessing challenge becomes quite daunting, in fact it pushes image analysis techniques right to their limits.

Cuprins

Preface. 1. Introduction. Part I: Generating hint. 2. A Model of Mammogram Image Formation. 3. A Model of Scattered Radiation. 4. A Model of Extra-Focal Radiation. 5. Estimating the Thickness of a Compressed Breast. 6. Model Verification and Sensitivity. Part II: Exploiting the hint Model. 7. Image Enhancement. 8. Disease Simulation. 9. Breast Compression. 10. Removing the Anti-scatter Grid. 11. Calcifications. 12. Curvilinear Structures. 13. Masses. Part III: Further Breast Image Analysis. 14. Breast MRI. 15. Other Modalities and Future Prospects.A: Receiver operating characteristic (ROC) curves. Bibliography. Index.