國立高雄大學圖資館 |

Language: English

Back

Machine learning in medical imaging14th International Workshop, MLMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings.Part II /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning in medical imagingedited by Xiaohuan Cao ... [et al.].
Reminder of title:	14th International Workshop, MLMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings.
remainder title:	MLMI 2023
other author:	Cao, Xiaohuan.
corporate name:
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xxi, 482 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer vision
Online resource:	https://doi.org/10.1007/978-3-031-45676-3
ISBN:	9783031456763$q(electronic bk.)

Machine learning in medical imaging14th International Workshop, MLMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings.Part II /
Machine learning in medical imaging14th International Workshop, MLMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings.Part II /[electronic resource] :MLMI 2023edited by Xiaohuan Cao ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xxi, 482 p. :ill., digital ;24 cm. - Lecture notes in computer science,143491611-3349 ;. - Lecture notes in computer science ;4891..

The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

ISBN: 9783031456763$q(electronic bk.)

Standard No.: 10.1007/978-3-031-45676-3doiSubjects--Topical Terms:

253837
Computer vision

LC Class. No.: TA1634

Dewey Class. No.: 006.37

Machine learning in medical imaging14th International Workshop, MLMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings.Part II /
LDR:02122nmm a2200349 a 4500 001 660536
003 DE-He213
005 20231014093616.0
006 m d
007 cr nn 008maaau
008 241106s2024 sz s 0 eng d
020 $a 9783031456763$q(electronic bk.)
020 $a 9783031456756$q(paper)
024 7 $a 10.1007/978-3-031-45676-3 $2 doi
035 $a 978-3-031-45676-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1634
072 7 $a UYT $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYT $2 thema
082 0 4 $a 006.37 $2 23
090 $a TA1634 $b .M685 2023
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Machine learning in medical imaging $h [electronic resource] : $b 14th International Workshop, MLMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings. $n Part II / $c edited by Xiaohuan Cao ... [et al.].
246 3 $a MLMI 2023
246 3 $a MICCAI 2023
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xxi, 482 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 1611-3349 ; $v 14349
520 $a The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
650 0 $a Computer vision $3 253837
650 0 $a Machine learning $v Congresses. $3 384498
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Computer Communication Networks. $3 218087
650 2 4 $a Computer Application in Social and Behavioral Sciences. $3 913134
650 2 4 $a Bioinformatics. $3 194415
700 1 $a Cao, Xiaohuan. $3 971842
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/10.1007/978-3-031-45676-3
950 $a Computer Science (SpringerNature-11645)