Biomedical Image Analysis (Record no. 85055)

000 -LEADER
fixed length control field 03682nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-031-02245-6
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730163846.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2009 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031022456
-- 978-3-031-02245-6
082 04 - CLASSIFICATION NUMBER
Call Number 620
100 1# - AUTHOR NAME
Author Acton, Scott.
245 10 - TITLE STATEMENT
Title Biomedical Image Analysis
Sub Title Segmentation /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2009.
300 ## - PHYSICAL DESCRIPTION
Number of Pages VIII, 107 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Image, Video, and Multimedia Processing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Parametric Active Contours -- Active Contours in a Bayesian Framework -- Geometric Active Contours -- Segmentation with Graph Algorithms -- Scale-Space Image Filtering for Segmentation.
520 ## - SUMMARY, ETC.
Summary, etc The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation.
700 1# - AUTHOR 2
Author 2 Ray, Nilanjan.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-02245-6
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2009.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Technology and Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical and Electronic Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1559-8144
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-- ZDB-2-SXSC

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