東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Data engineering in medical imaging ...

DEMI (Workshop) (2023 :)

Linked to FindBook

Google Book

Amazon

博客來

Data engineering in medical imaging = first MICCAI Workshop, DEMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data engineering in medical imaging/ edited by Binod Bhattarai ... [et al.].
Reminder of title:	first MICCAI Workshop, DEMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /
remainder title:	DEMI 2023
other author:	Bhattarai, Binod.
corporate name:	DEMI (Workshop)
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	x, 123 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Weakly Supervised Medical Image Segmentation through Dense Combinations of Dense Pseudo-Labels -- Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis -- A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentation -- Pre-training with simulated ultrasound images for breast mass segmentation and classification -- Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications -- A Self-supervised Approach for Detecting the Edges of Haustral Folds in Colonoscopy Video -- Procedurally Generated Colonoscopy and Laparoscopy Data For Improved Model Training Performance -- Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining -- A Study on Using Transformer Encoding Techniques to Optimize Data-driven Volume-to-Surface Registration for Minimally Invasive Liver Interventions -- Vision Transformer-based Self-Supervised Learning for Ulcerative Colitis Grading in Colonoscopy -- Task-guided Domain Gap Reduction for Monocular Depth Prediction in Endoscopy.
Contained By:	Springer Nature eBook
Subject:	Diagnostic imaging - Congresses. - Data processing -
Online resource:	https://doi.org/10.1007/978-3-031-44992-5
ISBN:	9783031449925

Data engineering in medical imaging = first MICCAI Workshop, DEMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /
Data engineering in medical imagingfirst MICCAI Workshop, DEMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /[electronic resource] :DEMI 2023edited by Binod Bhattarai ... [et al.]. - Cham :Springer Nature Switzerland :2023. - x, 123 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,143140302-9743 ;. - Lecture notes in computer science ;14314..

Weakly Supervised Medical Image Segmentation through Dense Combinations of Dense Pseudo-Labels -- Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis -- A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentation -- Pre-training with simulated ultrasound images for breast mass segmentation and classification -- Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications -- A Self-supervised Approach for Detecting the Edges of Haustral Folds in Colonoscopy Video -- Procedurally Generated Colonoscopy and Laparoscopy Data For Improved Model Training Performance -- Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining -- A Study on Using Transformer Encoding Techniques to Optimize Data-driven Volume-to-Surface Registration for Minimally Invasive Liver Interventions -- Vision Transformer-based Self-Supervised Learning for Ulcerative Colitis Grading in Colonoscopy -- Task-guided Domain Gap Reduction for Monocular Depth Prediction in Endoscopy.

Volume LNCS 14414 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada in October 2023. The DEMI 2023 proceedings contain 11 high-quality papers of 9 to 15 pages pre-selected through a rigorous peer review process (with an average of three reviews per paper) All submissions were peer-reviewed through a double-blind process by at least three members of the scientific review committee, comprising 16 experts in the field of medical imaging. The accepted manuscripts cover various medical image analysis methods and applications.

ISBN: 9783031449925

Standard No.: 10.1007/978-3-031-44992-5doiSubjects--Topical Terms:

893542
Diagnostic imaging
--Data processing--Congresses.

LC Class. No.: RC78.7.D53 / D38 2023

Dewey Class. No.: 616.0754

Data engineering in medical imaging = first MICCAI Workshop, DEMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /
LDR:02983nmm a2200361 a 4500 001 2334564
003 DE-He213
005 20230930122054.0
006 m d
007 cr nn 008maaau
008 240402s2023 sz s 0 eng d
020 $a 9783031449925 $q (electronic bk.)
020 $a 9783031449918 $q (paper)
024 7 $a 10.1007/978-3-031-44992-5 $2 doi
035 $a 978-3-031-44992-5
040 $a GP $c GP
041 0 $a eng
050 4 $a RC78.7.D53 $b D38 2023
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 616.0754 $2 23
090 $a RC78.7.D53 $b D378 2023
111 2 $a DEMI (Workshop) $n (1st : $d 2023 : $c Vancouver, B.C.) $3 3666267
245 1 0 $a Data engineering in medical imaging $h [electronic resource] : $b first MICCAI Workshop, DEMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings / $c edited by Binod Bhattarai ... [et al.].
246 3 $a DEMI 2023
246 3 $a MICCAI 2023
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2023.
300 $a x, 123 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 14314
505 0 $a Weakly Supervised Medical Image Segmentation through Dense Combinations of Dense Pseudo-Labels -- Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis -- A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentation -- Pre-training with simulated ultrasound images for breast mass segmentation and classification -- Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications -- A Self-supervised Approach for Detecting the Edges of Haustral Folds in Colonoscopy Video -- Procedurally Generated Colonoscopy and Laparoscopy Data For Improved Model Training Performance -- Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining -- A Study on Using Transformer Encoding Techniques to Optimize Data-driven Volume-to-Surface Registration for Minimally Invasive Liver Interventions -- Vision Transformer-based Self-Supervised Learning for Ulcerative Colitis Grading in Colonoscopy -- Task-guided Domain Gap Reduction for Monocular Depth Prediction in Endoscopy.
520 $a Volume LNCS 14414 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada in October 2023. The DEMI 2023 proceedings contain 11 high-quality papers of 9 to 15 pages pre-selected through a rigorous peer review process (with an average of three reviews per paper) All submissions were peer-reviewed through a double-blind process by at least three members of the scientific review committee, comprising 16 experts in the field of medical imaging. The accepted manuscripts cover various medical image analysis methods and applications.
650 0 $a Diagnostic imaging $x Data processing $v Congresses. $3 893542
650 1 4 $a Data Engineering. $3 3409361
650 2 4 $a Computer Science. $3 626642
700 1 $a Bhattarai, Binod. $3 3666268
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a International Conference on Medical Image Computing and Computer-Assisted Intervention $n (26th : $d 2023 : $c Vancouver, B.C. ; Online) $3 3666144
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 14314. $3 3666269
856 4 0 $u https://doi.org/10.1007/978-3-031-44992-5
950 $a Computer Science (SpringerNature-11645)