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Despeckling methods for medical ultr...

Zhang, Ju.

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Despeckling methods for medical ultrasound images

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Despeckling methods for medical ultrasound images/ by Ju Zhang, Yun Cheng.
作者:	Zhang, Ju.
其他作者:	Cheng, Yun.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	xv, 142 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Diagnostic ultrasonic imaging - Image quality. -
電子資源:	https://doi.org/10.1007/978-981-15-0516-4
ISBN:	9789811505164

Despeckling methods for medical ultrasound images
Zhang, Ju.

Despeckling methods for medical ultrasound images[electronic resource] /by Ju Zhang, Yun Cheng. - Singapore :Springer Singapore :2020. - xv, 142 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9789811505164

Standard No.: 10.1007/978-981-15-0516-4doiSubjects--Topical Terms:

3444498
Diagnostic ultrasonic imaging
--Image quality.

LC Class. No.: RC78.7.U4

Dewey Class. No.: 616.07543

Despeckling methods for medical ultrasound images
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505 0 $a 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.
520 $a 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.
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