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Intelligent vision in healthcare
~
Saraswat, Mukesh.
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Intelligent vision in healthcare
Record Type:
Electronic resources : Monograph/item
Title/Author:
Intelligent vision in healthcare/ edited 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.
[NT 15003449]:
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.
Contained By:
Springer Nature eBook
Subject:
Computer vision in medicine. -
Online resource:
https://doi.org/10.1007/978-981-16-7771-7
ISBN:
9789811677717
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
Standard No.: 10.1007/978-981-16-7771-7doiSubjects--Topical Terms:
2055159
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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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.
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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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Intelligent Technologies and Robotics (SpringerNature-42732)
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EB R859.7.C67 I57 2022
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