國立高雄大學圖資館 |

登入

回首頁

AI for brain lesion detection and trauma video action recognitionfirst BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI for brain lesion detection and trauma video action recognitionedited by Rina Bao ... [et al.].
其他題名:	first BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023 : proceedings /
其他題名:	MICCAI 2023
其他作者:	Bao, Rina.
團體作者:
出版者:	Cham :Springer Nature Switzerland :2025.
面頁冊數:	xiv, 95 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Diagnostic imagingCongresses.
電子資源:	https://doi.org/10.1007/978-3-031-71626-3
ISBN:	9783031716263$q(electronic bk.)

AI for brain lesion detection and trauma video action recognitionfirst BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023 : proceedings /
AI for brain lesion detection and trauma video action recognitionfirst BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023 : proceedings /[electronic resource] :MICCAI 2023edited by Rina Bao ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xiv, 95 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,145671611-3349 ;. - Lecture notes in computer science ;4891..

BONBID-HIE 2023 -- Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation -- Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy -- An Ensemble Approach for Segmentation of Neonatal HIE lesions -- Improving Segmentation of Hypoxic Ischemic Encephalopathy Lesions by Heavy Data Augmentation: Contribution to the BONBID Challenge -- A Deep Neural Network Approach for the Lesion Segmentation from Neonatal Brain Magnetic Resonance Imaging -- SegResNet based Reciprocal Transformation for BONBID-HIE Lesion Segmentation -- Trauma THOMPSON 2023 -- Overview of the Trauma THOMPSON Challenge at MICCAI 2023 -- The Trauma THOMPSON Challenge Report MICCAI 2023 -- Action Recognition and Action Anticipation Tasks in the Trauma THOMPSON Challenge Technical Report -- QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View.

This book constitutes the proceedings of the First BONBID-HIE Lesion Segmentation Challenge and the First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, in Vancouver, BC, Canada, during October 2023. For BONBID-HIE 2023 Challenge 6 papers have been accepted out of 14 submissions. They span a broad array of approaches leveraging anatomical information about HIE, data augmentation, training strategies, model architecture, and integration with traditional machine learning methods. For the TTC 2023 Trauma Thompson Challenge 4 accepted contributions are included in this book. They deal with advancements in machine learning methods and their practical applications in addressing small and diffuse lesions in HIE segmentation.

ISBN: 9783031716263$q(electronic bk.)

Standard No.: 10.1007/978-3-031-71626-3doiSubjects--Topical Terms:

387225
Diagnostic imaging
--Congresses.

LC Class. No.: RC78.7.D53

Dewey Class. No.: 616.0754

AI for brain lesion detection and trauma video action recognitionfirst BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023 : proceedings /
LDR:02956nmm a2200349 a 4500 001 678604
003 DE-He213
005 20241024125756.0
006 m d
007 cr nn 008maaau
008 251031s2025 sz s 0 eng d
020 $a 9783031716263$q(electronic bk.)
020 $a 9783031716256$q(paper)
024 7 $a 10.1007/978-3-031-71626-3 $2 doi
035 $a 978-3-031-71626-3
040 $a GP $c GP
041 0 $a eng
050 4 $a RC78.7.D53
072 7 $a UYT $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYT $2 thema
082 0 4 $a 616.0754 $2 23
090 $a RC78.7.D53 $b B699 2023
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a AI for brain lesion detection and trauma video action recognition $h [electronic resource] : $b first BONBID-HIE Lesion Segmentation Challenge and First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 16 and 12, 2023 : proceedings / $c edited by Rina Bao ... [et al.].
246 3 $a MICCAI 2023
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xiv, 95 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 1611-3349 ; $v 14567
505 0 $a BONBID-HIE 2023 -- Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation -- Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy -- An Ensemble Approach for Segmentation of Neonatal HIE lesions -- Improving Segmentation of Hypoxic Ischemic Encephalopathy Lesions by Heavy Data Augmentation: Contribution to the BONBID Challenge -- A Deep Neural Network Approach for the Lesion Segmentation from Neonatal Brain Magnetic Resonance Imaging -- SegResNet based Reciprocal Transformation for BONBID-HIE Lesion Segmentation -- Trauma THOMPSON 2023 -- Overview of the Trauma THOMPSON Challenge at MICCAI 2023 -- The Trauma THOMPSON Challenge Report MICCAI 2023 -- Action Recognition and Action Anticipation Tasks in the Trauma THOMPSON Challenge Technical Report -- QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View.
520 $a This book constitutes the proceedings of the First BONBID-HIE Lesion Segmentation Challenge and the First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, in Vancouver, BC, Canada, during October 2023. For BONBID-HIE 2023 Challenge 6 papers have been accepted out of 14 submissions. They span a broad array of approaches leveraging anatomical information about HIE, data augmentation, training strategies, model architecture, and integration with traditional machine learning methods. For the TTC 2023 Trauma Thompson Challenge 4 accepted contributions are included in this book. They deal with advancements in machine learning methods and their practical applications in addressing small and diffuse lesions in HIE segmentation.
650 0 $a Diagnostic imaging $v Congresses. $3 387225
650 0 $a Artificial intelligence $x Medical applications $v Congresses. $3 442992
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Artificial Intelligence. $3 212515
700 1 $a Bao, Rina. $3 991994
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/10.1007/978-3-031-71626-3
950 $a Computer Science (SpringerNature-11645)