國立高雄大學圖資館 |

登入

回首頁

Low field pediatric brain magnetic resonance image segmentation and quality assurancefirst MICCAI Challenge, LISA 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Low field pediatric brain magnetic resonance image segmentation and quality assuranceedited by Natasha Lepore, Marius George Linguraru.
其他題名:	first MICCAI Challenge, LISA 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /
其他題名:	LISA 2024
其他作者:	Lepore, Natasha.
團體作者:
出版者:	Cham :Springer Nature Switzerland :2025.
面頁冊數:	ix, 77 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	BrainAtlases.Magnetic resonance imaging
電子資源:	https://doi.org/10.1007/978-3-031-83008-2
ISBN:	9783031830082$q(electronic bk.)

Low field pediatric brain magnetic resonance image segmentation and quality assurancefirst MICCAI Challenge, LISA 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /
Low field pediatric brain magnetic resonance image segmentation and quality assurancefirst MICCAI Challenge, LISA 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /[electronic resource] :LISA 2024edited by Natasha Lepore, Marius George Linguraru. - Cham :Springer Nature Switzerland :2025. - ix, 77 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,155151611-3349 ;. - Lecture notes in computer science ;4891..

Open access.

This open access LNCS volume 15515 constitutes the refereed proceedings of the First MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024. The 6 full papers presented were carefully reviewed and selected from 8 submissions. This MICCAI Challenge focuses on the development and evaluation of automatic image analysis and machine learning algorithms and Ultra-low-field brain imaging has the potential to become a transformative tool for both clinical and research applications.

ISBN: 9783031830082$q(electronic bk.)

Standard No.: 10.1007/978-3-031-83008-2doiSubjects--Topical Terms:

713177
Brain
--Magnetic resonance imaging--Atlases.

LC Class. No.: RJ488.5.M33

Dewey Class. No.: 618.928047548

Low field pediatric brain magnetic resonance image segmentation and quality assurancefirst MICCAI Challenge, LISA 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings /
LDR:01936nmm a2200361 a 4500 001 679730
003 DE-He213
005 20250224115234.0
006 m d
007 cr nn 008maaau
008 251110s2025 sz s 0 eng d
020 $a 9783031830082$q(electronic bk.)
020 $a 9783031830105$q(paper)
024 7 $a 10.1007/978-3-031-83008-2 $2 doi
035 $a 978-3-031-83008-2
040 $a GP $c GP
041 0 $a eng
050 4 $a RJ488.5.M33
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 618.928047548 $2 23
090 $a RJ488.5.M33 $b L769 2024
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Low field pediatric brain magnetic resonance image segmentation and quality assurance $h [electronic resource] : $b first MICCAI Challenge, LISA 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings / $c edited by Natasha Lepore, Marius George Linguraru.
246 3 $a LISA 2024
246 3 $a MICCAI 2024
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a ix, 77 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 1611-3349 ; $v 15515
506 $a Open access.
520 $a This open access LNCS volume 15515 constitutes the refereed proceedings of the First MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024. The 6 full papers presented were carefully reviewed and selected from 8 submissions. This MICCAI Challenge focuses on the development and evaluation of automatic image analysis and machine learning algorithms and Ultra-low-field brain imaging has the potential to become a transformative tool for both clinical and research applications.
650 0 $a Brain $x Magnetic resonance imaging $v Atlases. $3 713177
650 0 $a Pediatric neurology $v Case studies. $3 446205
650 0 $a Artificial intelligence. $3 194058
650 0 $a Machine learning. $3 188639
650 1 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Machine Learning. $3 833608
700 1 $a Lepore, Natasha. $3 878397
700 1 $a Linguraru, Marius George. $3 560979
710 2 $a SpringerLink (Online service) $3 273601
711 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 4891. $3 383229
856 4 0 $u https://doi.org/10.1007/978-3-031-83008-2
950 $a Computer Science (SpringerNature-11645)