國立虎尾科技大學 |

Resource-Efficient Medical Image Analysis = First MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Resource-Efficient Medical Image Analysis/ edited by Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Huazhu Fu.
Reminder of title:	First MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings /
other author:	Xu, Xinxing.
Description:	X, 137 p. 42 illus., 39 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computer Application in Social and Behavioral Sciences. -
Online resource:	https://doi.org/10.1007/978-3-031-16876-5
ISBN:	9783031168765

Resource-Efficient Medical Image Analysis = First MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings /
Resource-Efficient Medical Image AnalysisFirst MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings /[electronic resource] :edited by Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Huazhu Fu. - 1st ed. 2022. - X, 137 p. 42 illus., 39 illus. in color.online resource. - Lecture Notes in Computer Science,135431611-3349 ;. - Lecture Notes in Computer Science,9324.

Multi-Task Semi-Supervised Learning for Vascular Network -- Segmentation and Renal Cell Carcinoma Classification -- Self-supervised Antigen Detection Artificial Intelligence (SANDI) -- RadTex: Learning Effcient Radiograph Representations from Text Reports -- Single Domain Generalization via Spontaneous Amplitude Spectrum Diversification -- Triple-View Feature Learning for Medical Image Segmentation -- Classification of 4D fMRI Images Using ML, Focusing on Computational and Memory Utilization Effciency -- An Effcient Defending Mechanism Against Image Attacking On Medical Image Segmentation Models -- Leverage Supervised and Self-supervised Pretrain Models for Pathological Survival Analysis via a Simple and Low-cost Joint Representation Tuning -- Pathological Image Contrastive Self-Supervised Learning -- Investigation of Training Multiple Instance Learning Networks with Instance Sampling -- Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound -- A self-attentive meta-learning approach for image-based few-shot disease detection -- Facing Annotation Redundancy: OCT Layer Segmentation with Only 10 Annotated Pixels Per Layer.

This book constitutes the refereed proceedings of the first MICCAI Workshop on Resource-Efficient Medical Image Analysis, REMIA 2022, held in conjunction with MICCAI 2022, in September 2022 as a hybrid event. REMIA 2022 accepted 13 papers from the 19 submissions received. The workshop aims at creating a discussion on the issues for practical applications of medical imaging systems with data, label and hardware limitations.

ISBN: 9783031168765

Standard No.: 10.1007/978-3-031-16876-5doiSubjects--Topical Terms:

1365738
Computer Application in Social and Behavioral Sciences.

LC Class. No.: TA1501-1820

Dewey Class. No.: 006

Resource-Efficient Medical Image Analysis = First MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings /
LDR:03171nam a22004215i 4500 001 1083151
003 DE-He213
005 20220910202840.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783031168765 $9 978-3-031-16876-5
024 7 $a 10.1007/978-3-031-16876-5 $2 doi
035 $a 978-3-031-16876-5
050 4 $a TA1501-1820
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 $2 23
245 1 0 $a Resource-Efficient Medical Image Analysis $h [electronic resource] : $b First MICCAI Workshop, REMIA 2022, Singapore, September 22, 2022, Proceedings / $c edited by Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Huazhu Fu.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2022.
300 $a X, 137 p. 42 illus., 39 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 Lecture Notes in Computer Science, $x 1611-3349 ; $v 13543
505 0 $a Multi-Task Semi-Supervised Learning for Vascular Network -- Segmentation and Renal Cell Carcinoma Classification -- Self-supervised Antigen Detection Artificial Intelligence (SANDI) -- RadTex: Learning Effcient Radiograph Representations from Text Reports -- Single Domain Generalization via Spontaneous Amplitude Spectrum Diversification -- Triple-View Feature Learning for Medical Image Segmentation -- Classification of 4D fMRI Images Using ML, Focusing on Computational and Memory Utilization Effciency -- An Effcient Defending Mechanism Against Image Attacking On Medical Image Segmentation Models -- Leverage Supervised and Self-supervised Pretrain Models for Pathological Survival Analysis via a Simple and Low-cost Joint Representation Tuning -- Pathological Image Contrastive Self-Supervised Learning -- Investigation of Training Multiple Instance Learning Networks with Instance Sampling -- Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound -- A self-attentive meta-learning approach for image-based few-shot disease detection -- Facing Annotation Redundancy: OCT Layer Segmentation with Only 10 Annotated Pixels Per Layer.
520 $a This book constitutes the refereed proceedings of the first MICCAI Workshop on Resource-Efficient Medical Image Analysis, REMIA 2022, held in conjunction with MICCAI 2022, in September 2022 as a hybrid event. REMIA 2022 accepted 13 papers from the 19 submissions received. The workshop aims at creating a discussion on the issues for practical applications of medical imaging systems with data, label and hardware limitations.
650 2 4 $a Computer Application in Social and Behavioral Sciences. $3 1365738
650 0 $a Image processing—Digital techniques. $3 1365735
650 0 $a Computer vision. $3 561800
650 0 $a Artificial intelligence. $3 559380
650 0 $a Education—Data processing. $3 1253610
650 0 $a Social sciences—Data processing. $3 1280453
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Computers and Education. $3 669806
700 1 $a Xu, Xinxing. $e editor. $1 https://orcid.org/0000-0003-1449-3072 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1389065
700 1 $a Li, Xiaomeng. $e editor. $1 https://orcid.org/0000-0003-1105-8083 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1389066
700 1 $a Mahapatra, Dwarikanath. $e editor. $1 https://orcid.org/0000-0001-9749-7858 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1389067
700 1 $a Cheng, Li. $e editor. $1 https://orcid.org/0000-0003-3261-3533 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1389068
700 1 $a Petitjean, Caroline. $e editor. $1 https://orcid.org/0000-0003-0013-5370 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1389069
700 1 $a Fu, Huazhu. $e editor. $1 https://orcid.org/0000-0002-9702-5524 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1297542
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783031168758
776 0 8 $i Printed edition: $z 9783031168772
830 0 $a Lecture Notes in Computer Science, $x 0302-9743 ; $v 9324 $3 1258960
856 4 0 $u https://doi.org/10.1007/978-3-031-16876-5
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)