Hybrid Machine Intelligence for Medical Image Analysis (Record no. 75940)

000 -LEADER
fixed length control field 04033nam a22006375i 4500
001 - CONTROL NUMBER
control field 978-981-13-8930-6
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801214102.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190808s2020 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811389306
-- 978-981-13-8930-6
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
245 10 - TITLE STATEMENT
Title Hybrid Machine Intelligence for Medical Image Analysis
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVI, 293 p. 179 illus., 114 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Preface -- Introduction -- Brain Tumor Segmentation from T1 Weighted MRI Images Using Rough Set Reduct and Quantum Inspired Particle Swarm Optimization -- Automated Region of Interest detection of Magnetic Resonance (MR) images by Center of Gravity (CoG) -- Brain tumors detection through low level features detection and rotation estimation -- Automatic MRI Image Segmentation for Brain tumors detection using Multilevel Sigmoid Activation (MUSIG) function -- Automatic Segmentation of pulmonary nodules in CT Images for Lung Cancer detection using self-supervised Neural Network Architecture -- A Hierarchical Fused Fuzzy Deep Neural Network for MRI Image Segmentation and Brain Tumor Classification -- Computer Aided Detection of Mammographic Lesions using Convolutional Neural Network (CNN) -- Conclusion.
520 ## - SUMMARY, ETC.
Summary, etc The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.
700 1# - AUTHOR 2
Author 2 Bhattacharyya, Siddhartha.
700 1# - AUTHOR 2
Author 2 Konar, Debanjan.
700 1# - AUTHOR 2
Author 2 Platos, Jan.
700 1# - AUTHOR 2
Author 2 Kar, Chinmoy.
700 1# - AUTHOR 2
Author 2 Sharma, Kalpana.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-13-8930-6
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2020.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer vision.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern recognition systems.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Vision.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automated Pattern Recognition.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-9503 ;
912 ## -
-- ZDB-2-ENG
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-- ZDB-2-SXE

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