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ORCID1st MILLanD@MICCAI 2022: Singapore
- Ghada Zamzmi
, Sameer K. Antani, Ulas Bagci, Marius George Linguraru, Sivaramakrishnan Rajaraman, Zhiyun Xue:
Medical Image Learning with Limited and Noisy Data - First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13559, Springer 2022, ISBN 978-3-031-16759-1
Efficient and Robust Annotation Strategies
- Chelsea Myers-Colet, Julien Schroeter, Douglas L. Arnold, Tal Arbel:
Heatmap Regression for Lesion Detection Using Pointwise Annotations. 3-12 - Bella Specktor-Fadida, Daphna Link-Sourani, Liat Ben-Sira, Elka Miller, Dafna Ben-Bashat, Leo Joskowicz:
Partial Annotations for the Segmentation of Large Structures with Low Annotation Cost. 13-22 - Hyeongsub Kim, Seo Taek Kong, Hongseok Lee, Kyungdoc Kim, Kyu-Hwan Jung:
Abstraction in Pixel-wise Noisy Annotations Can Guide Attention to Improve Prostate Cancer Grade Assessment. 23-31 - Zhuotong Cai, Jingmin Xin, Peiwen Shi, Sanping Zhou, Jiayi Wu, Nanning Zheng:
Meta Pixel Loss Correction for Medical Image Segmentation with Noisy Labels. 32-41 - Hanxiao Zhang, Xiao Gu, Minghui Zhang, Weihao Yu, Liang Chen, Zhexin Wang, Feng Yao, Yun Gu, Guang-Zhong Yang:
Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction. 42-51
Weakly-Supervised, Self-supervised, and Contrastive Learning
- Varun Naga, Tejas Sudharshan Mathai, Angshuman Paul, Ronald M. Summers:
Universal Lesion Detection and Classification Using Limited Data and Weakly-Supervised Self-training. 55-64 - Michael Gröger, Vadim Borisov, Gjergji Kasneci:
BoxShrink: From Bounding Boxes to Segmentation Masks. 65-75 - Xiao Qi, David J. Foran, John L. Nosher, Ilker Hacihaliloglu:
Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis. 76-85 - Sara Atito, Syed Muhammad Anwar, Muhammad Awais, Josef Kittler:
SB-SSL: Slice-Based Self-supervised Transformers for Knee Abnormality Classification from MRI. 86-95 - Camille Ruppli, Pietro Gori, Roberto Ardon, Isabelle Bloch:
Optimizing Transformations for Contrastive Learning in a Differentiable Framework. 96-105 - Bodong Zhang, Beatrice Knudsen, Deepika Sirohi, Alessandro Ferrero, Tolga Tasdizen:
Stain Based Contrastive Co-training for Histopathological Image Analysis. 106-116
Active and Continual Learning
- Suraj Kothawade, Atharv Savarkar, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer:
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification. 119-129 - Arijit Patra:
Real Time Data Augmentation Using Fractional Linear Transformations in Continual Learning. 130-140 - Suraj Kothawade, Akshit Shrivastava, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer:
DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures. 141-150
Transfer Representation Learning
- Peidi Xu, Faezeh Moshfeghifar, Torkan Gholamalizadeh, Michael Bachmann Nielsen, Kenny Erleben, Sune Darkner:
Auto-segmentation of Hip Joints Using MultiPlanar UNet with Transfer Learning. 153-162 - Zhenjie Cao, Xiaoyun Zhou, Yuxing Tang, Mei Han, Jing Xiao, Jie Ma, Peng Chang:
Asymmetry and Architectural Distortion Detection with Limited Mammography Data. 163-173
Imbalanced Data and Out-of-Distribution Generalization
- Peter D. Erickson, Tejas Sudharshan Mathai, Ronald M. Summers:
Class Imbalance Correction for Improved Universal Lesion Detection and Tagging in CT. 177-186 - Xiaoyuan Guo, Judy Wawira Gichoya, Saptarshi Purkayastha, Imon Banerjee:
CVAD: An Anomaly Detector for Medical Images Based on Cascade VAE. 187-196
Approaches for Noisy, Missing, and Low Quality Data
- Quang T. M. Pham, Jong Chul Han, Jitae Shin:
Visual Field Prediction with Missing and Noisy Data Based on Distance-Based Loss. 199-205 - Zhiyun Xue, Sandeep Angara, Peng Guo, Sivaramakrishnan Rajaraman, Jose Jeronimo, Ana Cecilia Rodriguez, Karla Alfaro, Kittipat Charoenkwan, Chemtai Mungo, Joel Fokom Domgue, Nicolas Wentzensen, Kanan T. Desai, Olusegun Kayode Ajenifuja, Elisabeth Wikstrom, Brian Befano, Silvia De Sanjosé, Mark Schiffman, Sameer K. Antani:
Image Quality Classification for Automated Visual Evaluation of Cervical Precancer. 206-217 - Dongyang Kuang, Craig Michoski, Wenting Li, Rui Guo:
A Monotonicity Constrained Attention Module for Emotion Classification with Limited EEG Data. 218-228 - Yung-Chieh Chan, Jerry Zhang, Katie Frizzi, Nigel Calcutt, Garrison W. Cottrell:
Automated Skin Biopsy Analysis with Limited Data. 229-238
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