Medical Image Learning with Limited and Noisy Data (Record no. 96353)

000 -LEADER
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001 - CONTROL NUMBER
control field 978-3-031-44917-8
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730201033.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231007s2023 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031449178
-- 978-3-031-44917-8
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-44917-8
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1501-1820
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1634
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYT
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM016000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYT
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006
Edition number 23
245 10 - TITLE STATEMENT
Title Medical Image Learning with Limited and Noisy Data
Medium [electronic resource] :
Remainder of title Second International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings /
Statement of responsibility, etc. edited by Zhiyun Xue, Sameer Antani, Ghada Zamzmi, Feng Yang, Sivaramakrishnan Rajaraman, Sharon Xiaolei Huang, Marius George Linguraru, Zhaohui Liang.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer Nature Switzerland :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2023.
300 ## - PHYSICAL DESCRIPTION
Extent XI, 270 p. 77 illus., 72 illus. in color.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume/sequential designation 14307
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Efficient Annotation and Training Strategies -- Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-quality Annotations -- ScribSD: Scribble-supervised Fetal MRI Segmentation based on Simultaneous Feature and Prediction Self-Distillation -- Label-efficient Contrastive Learning-based Model for Nuclei Detection and Classification in 3D Cardiovascular Immunofluorescent Images -- Affordable Graph Neural Network Framework using Topological Graph Contraction -- Approaches for Noisy, Missing, and Low Quality Data -- Dual-domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-angle Reconstruction of Low-dose Cardiac SPECT -- A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain Imaging -- COVID-19 Lesion Segmentation Framework for the Contrast-enhanced CT in the Absence of Contrast-enhanced CT Annotation -- Feasibility of Universal Anomaly Detection without Knowingthe Abnormality in Medical Image -- Unsupervised, Self-supervised, and Contrastive Learning -- Decoupled Conditional Contrastive Learning with Variable Metadata for Prostate Lesion Detection -- FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation -- Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation Microscopy -- Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning -- SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction -- Robust Unsupervised Image to Template Registration Without Image Similarity Los -- A Dual-Branch Network with Mixed and Self-Supervision for Medical Image Segmentation: An Application to Segment Edematous Adipose Tissue -- Weakly-supervised, Semi-supervised, and Multitask Learning -- Combining Weakly Supervised Segmentation with Multitask Learning forImproved 3D MRI Brain Tumour Classification -- Exigent Examiner and Mean Teacher: An Advanced 3D CNN-based Semi-Supervised Brain Tumor Segmentation Framework -- Extremely Weakly-supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation -- Multi-Task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Image -- Active Learning -- Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach -- Test-time Augmentation-based Active Learning and Self-training for Label-efficient Segmentation -- Active Transfer Learning for 3D Hippocampus Segmentation -- Transfer Learning -- Using Training Samples as Transitive Information Bridges in Predicted 4D MRI -- To Pretrain or not to Pretrain? A Case Study of Domain-Specific Pretraining for Semantic Segmentation in Histopathology -- Large-scale Pretraining on Pathological Images for Fine-tuning of Small Pathological Benchmarks.
520 ## - SUMMARY, ETC.
Summary, etc. This book consists of full papers presented in the 2nd workshop of "Medical Image Learning with Noisy and Limited Data (MILLanD)" held in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). The 24 full papers presented were carefully reviewed and selected from 38 submissions. The conference focused on challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Image processing
General subdivision Digital techniques.
9 (RLIN) 4145
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer vision.
9 (RLIN) 165826
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Imaging, Vision, Pattern Recognition and Graphics.
9 (RLIN) 31569
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Xue, Zhiyun.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165827
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Antani, Sameer.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165828
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zamzmi, Ghada.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165829
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Yang, Feng.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165830
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Rajaraman, Sivaramakrishnan.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165831
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Huang, Sharon Xiaolei.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165832
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Linguraru, Marius George.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165833
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Liang, Zhaohui.
Relator term editor.
Relationship edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 165834
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
9 (RLIN) 165835
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031449185
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031471964
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume/sequential designation 14307
9 (RLIN) 23263
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-44917-8">https://doi.org/10.1007/978-3-031-44917-8</a>
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Koha item type eBooks-Lecture Notes in CS

No items available.