Medical image learning with limited ...
MILLanD (Workshop) (2022 :)

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  • Medical image learning with limited and noisy data = first International Workshop, MILLanD 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022 : proceedings /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Medical image learning with limited and noisy data/ edited by Ghada Zamzmi ... [et al.].
    其他題名: first International Workshop, MILLanD 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022 : proceedings /
    其他題名: MILLanD 2022
    其他作者: Zamzmi, Ghada.
    團體作者: MILLanD (Workshop)
    出版者: Cham :Springer Nature Switzerland : : 2022.,
    面頁冊數: xi, 240 p. :ill. (chiefly color), digital ;24 cm.
    內容註: 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.
    Contained By: Springer Nature eBook
    標題: Imaging systems in medicine - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-16760-7
    ISBN: 9783031167607
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W9445502 電子資源 11.線上閱覽_V 電子書 EB R857.O6 M55 2022 一般使用(Normal) 在架 0
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