Prediction and Classification of Respiratory Motion (Record no. 27722)

MARC details
000 -LEADER
fixed length control field 04125nam a22004815i 4500
001 - CONTROL NUMBER
control field 978-3-642-41509-8
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20170628040135.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131025s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642415098
-- 978-3-642-41509-8
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-642-41509-8
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q342
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Lee, Suk Jin.
Relator term author.
245 10 - TITLE STATEMENT
Title Prediction and Classification of Respiratory Motion
Medium [electronic resource] /
Statement of responsibility, etc by Suk Jin Lee, Yuichi Motai.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2014.
300 ## - PHYSICAL DESCRIPTION
Extent IX, 167 p. 67 illus., 65 illus. in color.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
International Standard Serial Number 1860-949X ;
Volume number/sequential designation 525
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Review: Prediction of Respiratory Motion -- Phantom: Prediction of Human Motion with Distributed Body Sensors -- Respiratory Motion Estimation with Hybrid Implementation -- Customized Prediction of Respiratory Motion -- Irregular Breathing Classification from Multiple Patient Datasets -- Conclusions and Contributions.
520 ## - SUMMARY, ETC.
Summary, etc This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin. In the first chapter following the Introduction  to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study—prediction of human motion with distributed body sensors—using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and the tracking estimation value. The experimental results of 448 patients’ breathing patterns validated the proposed irregular breathing classifier in the last chapter.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Medical records
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Health Informatics.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Motai, Yuichi.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642415081
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Studies in Computational Intelligence,
-- 1860-949X ;
Volume number/sequential designation 525
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-3-642-41509-8">http://dx.doi.org/10.1007/978-3-642-41509-8</a>
912 ## -
-- ZDB-2-ENG
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Central Library Central Library 28/06/2017 Springer EBook   E-50901 28/06/2017 28/06/2017 E-Book

Maintained by VTU Library