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Despeckling Methods for Medical Ultrasound Images / by Ju Zhang, Yun Cheng.
Author
Zhang, Ju.
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Format
Book
Language
English
Εdition
1st ed. 2020.
Published/Created
Singapore : Springer Singapore : Imprint: Springer, 2020.
Description
1 online resource (154 pages)
Details
Subject(s)
Signal processing
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Image processing
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Speech processing systems
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Biomedical engineering
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Radiology
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Author
Cheng, Yun
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Cheng, Yun
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Cheng, Yun
[Browse]
Summary note
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.
Contents
Introductions
Despeckle Filters for Medical Ultrasound Images
Wavelet and Fast Bilateral Filter Based Despeckling Method for Medical Ultrasound Images
Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter
Despeckling Method for Medical Images Based on Wavelet and Trilateral Filter
Nonsubsampled Shearlet and Guided Filter Based Despeckling Method for Medical Ultrasound Images. .
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ISBN
981-15-0516-0
Doi
10.1007/978-981-15-0516-4
Statement on responsible collection description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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