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Domain adaptation and representation transfer : 4th MICCAI Workshop, DART 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings / Konstantinos Kamnitsas, Lisa Koch, Mobarakol Islam, Ziyue Xu, Jorge Cardoso, Qi Dou, Nicola Rieke, Sotirios Tsaftaris (eds.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 13542.Publisher: Cham : Springer, [2022]Copyright date: ©2022Description: 1 online resource (x, 147 pages) : illustrations (chiefly color)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031168529
  • 3031168526
  • 9788303116857
  • 8303116851
Other title:
  • DART 2022
Subject(s): Genre/Form: Additional physical formats: No titleDDC classification:
  • 616.07/54 23/eng/20220928
LOC classification:
  • RC78.7.D53
Online resources:
Contents:
Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification -- Benchmarking Transformers for Medical Image Classification -- Supervised domain adaptation using gradients transfer for improved medical image analysis -- Stain-AgLr: Stain Agnostic Learning for Computational Histopathology using Domain Consistency and Stain Regeneration Loss -- MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation -- Unsupervised site adaptation by intra-site variability alignment -- Discriminative, Restorative, and Adversarial Learning: Stepwise Incremental Pretraining -- POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis -- Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging -- Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images -- Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts -- Adaptive Optimization with Fewer Epochs Improves Across-Scanner Generalization of U-Net based Medical Image Segmentation -- CateNorm: Categorical Normalization for Robust Medical Image Segmentation.
Summary: This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022. DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. .
Holdings
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Total holds: 0

International conference proceedings.

Includes author index.

This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022. DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. .

Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification -- Benchmarking Transformers for Medical Image Classification -- Supervised domain adaptation using gradients transfer for improved medical image analysis -- Stain-AgLr: Stain Agnostic Learning for Computational Histopathology using Domain Consistency and Stain Regeneration Loss -- MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation -- Unsupervised site adaptation by intra-site variability alignment -- Discriminative, Restorative, and Adversarial Learning: Stepwise Incremental Pretraining -- POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis -- Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging -- Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images -- Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts -- Adaptive Optimization with Fewer Epochs Improves Across-Scanner Generalization of U-Net based Medical Image Segmentation -- CateNorm: Categorical Normalization for Robust Medical Image Segmentation.

Online resource; title from PDF title page (SpringerLink, viewed September 28, 2022).

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