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Intelligent vision in healthcare

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent vision in healthcareedited by Mukesh Saraswat, Harish Sharma, Karm Veer Arya.
other author:	Saraswat, Mukesh.
Published:	Singapore :Springer Singapore :2022.
Description:	xiii, 151 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer vision in medicine.
Online resource:	https://doi.org/10.1007/978-981-16-7771-7
ISBN:	9789811677717$q(electronic bk.)

Intelligent vision in healthcare
Intelligent vision in healthcare[electronic resource] /edited by Mukesh Saraswat, Harish Sharma, Karm Veer Arya. - Singapore :Springer Singapore :2022. - xiii, 151 p. :ill., digital ;24 cm. - Studies in autonomic, data-driven and industrial computing,2730-6445. - Studies in autonomic, data-driven and industrial computing..

Intelligent Vision in Healthcare -- Diagnosis of Covid-19 in X-ray and CT Images Using Online Clustering Framework -- Unsupervised Deep Learning Approach for the Identiﬁcation of Intracranial haemorrhage in CT images using PCA-Net and K-Means algorithm -- Automatic segmentation of optic cup and optic disc using MultiResUnet for Glaucoma classification from fundus image -- A Framework to Classify the Calciﬁcation Region from USG Images of Thyroid Nodules -- Predicting Heart Disease with Multiple Classifiers.

This book focuses on various aspects of computer vision applications in the field of healthcare. It covers new tools and technologies in some of the important areas of medical science like histopathological image analysis, cancer taxonomy, use of deep learning architecture dental care, and many more. Furthermore, this book reviews and discusses the use of intelligent learning-based algorithms for increasing the precision in medical domain. The book discusses different computer vision algorithms which are useful in various industries and day-to-day life. It also highlights many challenges faced by research community, like view point variations, scale variations, illumination variations, multi-modalities, and noise.

ISBN: 9789811677717$q(electronic bk.)

Standard No.: 10.1007/978-981-16-7771-7doiSubjects--Topical Terms:

567209
Computer vision in medicine.

LC Class. No.: R859.7.C67 / I57 2022

Dewey Class. No.: 610.285637

Intelligent vision in healthcare
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505 0 $a Intelligent Vision in Healthcare -- Diagnosis of Covid-19 in X-ray and CT Images Using Online Clustering Framework -- Unsupervised Deep Learning Approach for the Identiﬁcation of Intracranial haemorrhage in CT images using PCA-Net and K-Means algorithm -- Automatic segmentation of optic cup and optic disc using MultiResUnet for Glaucoma classification from fundus image -- A Framework to Classify the Calciﬁcation Region from USG Images of Thyroid Nodules -- Predicting Heart Disease with Multiple Classifiers.
520 $a This book focuses on various aspects of computer vision applications in the field of healthcare. It covers new tools and technologies in some of the important areas of medical science like histopathological image analysis, cancer taxonomy, use of deep learning architecture dental care, and many more. Furthermore, this book reviews and discusses the use of intelligent learning-based algorithms for increasing the precision in medical domain. The book discusses different computer vision algorithms which are useful in various industries and day-to-day life. It also highlights many challenges faced by research community, like view point variations, scale variations, illumination variations, multi-modalities, and noise.
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650 2 4 $a Health Informatics. $3 274212
700 1 $a Saraswat, Mukesh. $3 917828
700 1 $a Sharma, Harish. $3 860956
700 1 $a Arya, Karm Veer. $3 818719
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