Medical Image Learning with Limited and Noisy Data (Record no. 173617)

MARC details
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001 - CONTROL NUMBER
control field 978-3-031-16760-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125038.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031167607
-- 978-3-031-16760-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-16760-7
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
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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 First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings /
Statement of responsibility, etc edited by Ghada Zamzmi, Sameer Antani, Ulas Bagci, Marius George Linguraru, Sivaramakrishnan Rajaraman, Zhiyun Xue.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2022.
264 #1 -
-- Cham :
-- Springer Nature Switzerland :
-- Imprint: Springer,
-- 2022.
300 ## - PHYSICAL DESCRIPTION
Extent XI, 240 p. 77 illus., 71 illus. in color.
Other physical details online resource.
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490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume number/sequential designation 13559
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Efficient and Robust Annotation Strategies -- Heatmap Regression for Lesion Detection using Pointwise Annotations.- -- Partial Annotations for the Segmentation of Large Structures with Low Annotation.- -- Abstraction in Pixel-wise Noisy Annotations Can Guide Attention to Improve Prostate Cancer Grade Assessment -- Meta Pixel Loss Correction for Medical Image Segmentation with Noisy Labels -- Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction -- Weakly-supervised, Self-supervised, and Contrastive Learning -- Universal Lesion Detection and Classification using Limited Data and Weakly-Supervised Self-Training -- BoxShrink: From Bounding Boxes to Segmentation Masks -- Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis -- SB-SSL: Slice-Based Self-Supervised Transformers for Knee Abnormality Classification from MRI -- Optimizing Transformations for Contrastive Learning in a Differentiable Framework.-Stain-based Contrastive Co-training for Histopathological Image Analysis -- Active and Continual Learning -- CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification -- Real-time Data Augmentation using Fractional Linear Transformations in Continual Learning -- DIAGNOSE: Avoiding Out-of-distribution Data using Submodular Information Measures -- Transfer Representation Learning -- Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning -- Asymmetry and Architectural Distortion Detection with Limited Mammography Data -- Imbalanced Data and Out-of-distribution Generalization -- Class Imbalance Correction for Improved Universal Lesion Detection and Tagging in CT -- CVAD: An Anomaly Detector for Medical Images Based on Cascade -- Approaches for Noisy, Missing, and Low Quality Data -- Visual Field Prediction with Missing and Noisy Data Based on Distance-based Loss -- Image Quality Classification for Automated Visual Evaluation of Cervical Precancer -- A Monotonicity Constraint Attention Module for Emotion Classification with Limited EEG Data -- Automated Skin Biopsy Analysis with Limited Data.
520 ## - SUMMARY, ETC.
Summary, etc This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the 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 as entry element Image processing
General subdivision Digital techniques.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer vision.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Imaging, Vision, Pattern Recognition and Graphics.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zamzmi, Ghada.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Antani, Sameer.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Bagci, Ulas.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Linguraru, Marius George.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Rajaraman, Sivaramakrishnan.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Xue, Zhiyun.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031167591
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031167614
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Computer Science,
-- 1611-3349 ;
Volume number/sequential designation 13559
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-16760-7">https://doi.org/10.1007/978-3-031-16760-7</a>
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Koha item type eBooks-CSE-Springer

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