Despeckling Methods for Medical Ultrasound Images [electronic resource] / by Ju Zhang, Yun Cheng.

9789811505164

1st ed. 2020.

Singapore : Springer Singapore : Imprint: Springer, 2020.

1 online resource (XV, 142 p.) 80 illus., 38 illus. in color.

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Based upon the research they have conducted over the past decade in the field of denoising processes for medical ultrasonic imaging, in this book, the authors systematically present despeckling methods for medical ultrasonic images. Firstly, the respective methods are reviewed and divided into five categories. Secondly, after introducing some basic mathematical tools such as wavelet and shearlet transforms, the authors highlight five recently developed despeckling methods for medical ultrasonic images. In turn, simulations and experiments for clinical ultrasonic images are presented for each method, and comparison studies with other well-known existing methods are conducted, showing the effectiveness and superiority of the new methods. Students and researchers in the field of signal and image processing, as well as medical professionals whose work involves ultrasonic diagnosis, will greatly benefit from this book. Familiarizing them with the state of the art in despeckling methods for medical ultrasonic images, it offers a useful reference guide for their study and research work.

Springer ENIN.

Books / Online

English

January 07, 2020