國立虎尾科技大學 |

Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges = 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges/ edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi.
Reminder of title:	9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers /
other author:	Pop, Mihaela.
Description:	XIV, 487 p. 216 illus., 192 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Optical data processing. -
Online resource:	https://doi.org/10.1007/978-3-030-12029-0
ISBN:	9783030120290

Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges = 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers /
Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers /[electronic resource] :edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi. - 1st ed. 2019. - XIV, 487 p. 216 illus., 192 illus. in color.online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11395. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;9219.

Cardiac imaging and image processing -- Machine learning applied to cardiac imaging and image analysis -- Atlas construction -- Statistical modelling of cardiac function across different patient populations -- Cardiac computational physiology -- Model customization -- Atlas based functional analysis -- Ontological schemata for data and results -- Integrated functional and structural analyses -- Pre-clinical and clinical applicability of these methods.

This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

ISBN: 9783030120290

Standard No.: 10.1007/978-3-030-12029-0doiSubjects--Topical Terms:

639187
Optical data processing.

LC Class. No.: TA1630-1650

Dewey Class. No.: 006.6

Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges = 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers /
LDR:03125nam a22004335i 4500 001 1014199
003 DE-He213
005 20200704230139.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030120290 $9 978-3-030-12029-0
024 7 $a 10.1007/978-3-030-12029-0 $2 doi
035 $a 978-3-030-12029-0
050 4 $a TA1630-1650
072 7 $a UYT $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a UYT $2 thema
072 7 $a UYQV $2 thema
082 0 4 $a 006.6 $2 23
082 0 4 $a 006.37 $2 23
245 1 0 $a Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges $h [electronic resource] : $b 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / $c edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XIV, 487 p. 216 illus., 192 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Image Processing, Computer Vision, Pattern Recognition, and Graphics ; $v 11395
505 0 $a Cardiac imaging and image processing -- Machine learning applied to cardiac imaging and image analysis -- Atlas construction -- Statistical modelling of cardiac function across different patient populations -- Cardiac computational physiology -- Model customization -- Atlas based functional analysis -- Ontological schemata for data and results -- Integrated functional and structural analyses -- Pre-clinical and clinical applicability of these methods.
520 $a This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.
650 0 $a Optical data processing. $3 639187
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computer communication systems. $3 1115394
650 0 $a Data mining. $3 528622
650 1 4 $a Image Processing and Computer Vision. $3 670819
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Computer Communication Networks. $3 669310
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
700 1 $a Pop, Mihaela. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1143176
700 1 $a Sermesant, Maxime. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 898478
700 1 $a Zhao, Jichao. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1308426
700 1 $a Li, Shuo. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1023125
700 1 $a McLeod, Kristin. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1304188
700 1 $a Young, Alistair. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1264816
700 1 $a Rhode, Kawal. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1264815
700 1 $a Mansi, Tommaso. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1250334
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030120283
776 0 8 $i Printed edition: $z 9783030120306
830 0 $a Image Processing, Computer Vision, Pattern Recognition, and Graphics ; $v 9219 $3 1253644
856 4 0 $u https://doi.org/10.1007/978-3-030-12029-0
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
912 $a ZDB-2-LNC
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)