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Computer-aided intelligent diagnosis of skin melanoma

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computer-aided intelligent diagnosis of skin melanoma/ by Shuli Guo, Xiaowei Song, Lina Han.
Author:	Guo, Shuli.
other author:	Song, Xiaowei.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xvii, 132 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Skin - Cancer -
Online resource:	https://doi.org/10.1007/978-981-96-6135-0
ISBN:	9789819661350

Computer-aided intelligent diagnosis of skin melanoma
Guo, Shuli.

Computer-aided intelligent diagnosis of skin melanoma[electronic resource] /by Shuli Guo, Xiaowei Song, Lina Han. - Singapore :Springer Nature Singapore :2025. - xvii, 132 p. :ill. (chiefly color), digital ;24 cm.

Introduction -- Color correction based on gamma correction and multi-scale image fusion -- Hair removal from dermoscopic images based on maximum variance fuzzy clustering and improved Criminisi algorithm -- Hair removal from dermoscopic images based on texture spectrum iterative tensor voting and optimized total variation algorithm -- Dermoscopic image registration based on adaptive SURF feature extraction and weighted nuclear norm minimization fusion.

This book is intended primarily for researchers, engineers, and graduate students in the fields of medicine management and software engineering in the field of dermatology. Aiming at the problems of color deviation, structured noise interference, and uneven distribution of feature points in the identification of melanoma, this book researches four aspects of dermoscopic image such as color correction, hair removal, image registration and classification recognition. Some creative methods are presented as follows, 1 Dermoscopic image color correction, 2 Dermoscopic image hair removal, 3 Dermoscopic image registration. In writing style, a combination of diagrams, tables, formula and text is used in order that the book can be understood easily and raise the readers' interest, and in content, theoretical analysis and medical application are combined to describe the advanced technologies in every chapter.

ISBN: 9789819661350

Standard No.: 10.1007/978-981-96-6135-0doiSubjects--Topical Terms:

781236
Skin
--Cancer

LC Class. No.: RC280.S5

Dewey Class. No.: 616.99477

Computer-aided intelligent diagnosis of skin melanoma
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505 0 $a Introduction -- Color correction based on gamma correction and multi-scale image fusion -- Hair removal from dermoscopic images based on maximum variance fuzzy clustering and improved Criminisi algorithm -- Hair removal from dermoscopic images based on texture spectrum iterative tensor voting and optimized total variation algorithm -- Dermoscopic image registration based on adaptive SURF feature extraction and weighted nuclear norm minimization fusion.
520 $a This book is intended primarily for researchers, engineers, and graduate students in the fields of medicine management and software engineering in the field of dermatology. Aiming at the problems of color deviation, structured noise interference, and uneven distribution of feature points in the identification of melanoma, this book researches four aspects of dermoscopic image such as color correction, hair removal, image registration and classification recognition. Some creative methods are presented as follows, 1 Dermoscopic image color correction, 2 Dermoscopic image hair removal, 3 Dermoscopic image registration. In writing style, a combination of diagrams, tables, formula and text is used in order that the book can be understood easily and raise the readers' interest, and in content, theoretical analysis and medical application are combined to describe the advanced technologies in every chapter.
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