Detection of Early Features of Cancer in Mammography

Approximately one in nine women in the Western world
will develop breast cancer, making it one of the
most common and terrifying cancers. Screening
programs reduce the mortality rate, but introduce an
enormous amount of information that radiologists
must process on a daily basis. Computer-aided
diagnosis can assist clinicians sort through this
data and help detect and classify cancer. This
monograph introduces original results for the
detection of early features of breast cancer from X-
ray mammography analysis. Some of the earliest signs
of breast cancer are clusters of
microcalcifications, and a method for their
detection based on a model of the human visual
system is presented. The detection of breast masses
in temporal mammographic pairs is also investigated.
Image normalization and its benefits for cancer
detection is another key concept discussed in this
book, along with screening programs and other
imaging modalities for breast cancer detection. The
subject is of immense importance, not just to
radiologists and clinicians, but to physicists,
researchers, students and anyone who has been
touched by this terrible disease.

Autorentext

DPhil, MA, MS, Staff Scientist in Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, USA. Studied at University of Oxford, UK; University of Sibiu, Romania. Researcher at Harvard University, USA; INRIA, France. Taught at University of Nice, France, University of Oxford; University of Sibiu.

Klappentext

Approximately one in nine women in the Western world will develop breast cancer, making it one of the most common and terrifying cancers. Screening programs reduce the mortality rate, but introduce an enormous amount of information that radiologists must process on a daily basis. Computer-aided diagnosis can assist clinicians sort through this data and help detect and classify cancer. This monograph introduces original results for the detection of early features of breast cancer from X- ray mammography analysis. Some of the earliest signs of breast cancer are clusters of microcalcifications, and a method for their detection based on a model of the human visual system is presented. The detection of breast masses in temporal mammographic pairs is also investigated. Image normalization and its benefits for cancer detection is another key concept discussed in this book, along with screening programs and other imaging modalities for breast cancer detection. The subject is of immense importance, not just to radiologists and clinicians, but to physicists, researchers, students and anyone who has been touched by this terrible disease.