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MOVI@MICCAI 2022: Singapore
- Yuankai Huo
, Bryan A. Millis
Medical Optical Imaging and Virtual Microscopy Image Analysis - First International Workshop, MOVI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Lecture Notes in Computer Science 13578, Springer 2022, ISBN 978-3-031-16960-1 - Yue Guo, David Borland
Cell Counting with Inverse Distance Kernel and Self-supervised Learning. 1-10 - Souradeep Chakraborty, Rajarsi Gupta, Ke Ma, Darshana Govind
Predicting the Visual Attention of Pathologists Evaluating Whole Slide Images of Cancer. 11-21 - Youssef Dawoud, Katharina Ernst, Gustavo Carneiro
Edge-Based Self-supervision for Semi-supervised Few-Shot Microscopy Image Cell Segmentation. 22-31 - Colin S. C. Tsang
Joint Denoising and Super-Resolution for Fluorescence Microscopy Using Weakly-Supervised Deep Learning. 32-41 - Shunxing Bao, Jia Li
MxIF Q-score: Biology-Informed Quality Assurance for Multiplexed Immunofluorescence Imaging. 42-52 - Alessandro Ferrero, Beatrice Knudsen, Deepika Sirohi, Ross T. Whitaker:
A Pathologist-Informed Workflow for Classification of Prostate Glands in Histopathology. 53-62 - Litao Yang, Deval Mehta, Dwarikanath Mahapatra, Zongyuan Ge:
Leukocyte Classification Using Multimodal Architecture Enhanced by Knowledge Distillation. 63-72 - Maximilian Fischer, Peter Neher
Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models. 73-83 - Kristofer E. delas Peñas, Ralf Haeusler, Sally Feng
Profiling DNA Damage in 3D Histology Samples. 84-93 - Surojit Saha, Ouk Choi, Ross T. Whitaker:
Few-Shot Segmentation of Microscopy Images Using Gaussian Process. 94-104 - Huaqian Wu, Nicolas Souedet, Camille Mabillon, Caroline Jan, Cédric Clouchoux, Thierry Delzescaux:
Adversarial Stain Transfer to Study the Effect of Color Variation on Cell Instance Segmentation. 105-114 - Vaanathi Sundaresan, Julia F. Lehman, Sean P. Fitzgibbon, Saâd Jbabdi, Suzanne N. Haber, Anastasia Yendiki:
Constrained Self-supervised Method with Temporal Ensembling for Fiber Bundle Detection on Anatomic Tracing Data. 115-125 - Haleh Akrami, Tosha Shah, Amir Vajdi, Andrew Brown, Radha Krishnan, Razvan Cristescu, Antong Chen:
Sequential Multi-task Learning for Histopathology-Based Prediction of Genetic Mutations with Extremely Imbalanced Labels. 126-135 - Gozde N. Gunesli, Robert Jewsbury, Shan-E-Ahmed Raza, Nasir M. Rajpoot:
Morph-Net: End-to-End Prediction of Nuclear Morphological Features from Histology Images. 136-144 - Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green
A Light-Weight Interpretable Model for Nuclei Detection and Weakly-Supervised Segmentation. 145-155 - Ziheng Yang, Halim Benhabiles, Féryal Windal, Jérôme Follet, Anne-Charlotte Leniere, Dominique Collard:
A Coarse-to-Fine Segmentation Methodology Based on Deep Networks for Automated Analysis of Cryptosporidium Parasite from Fluorescence Microscopic Images. 156-166 - Chunlun Xiao, Mingzhu Li, Liangge He, Xuegang Song, Tianfu Wang, Baiying Lei
Swin Faster R-CNN for Senescence Detection of Mesenchymal Stem Cells in Bright-Field Images. 167-176 - Veena Kaustaban, Qinle Ba, Ipshita Bhattacharya, Nahil Sobh, Satarupa Mukherjee, Jim Martin, Mohammad Saleh Miri, Christoph Guetter, Amal Chaturvedi:
Characterizing Continual Learning Scenarios for Tumor Classification in Histopathology Images. 177-187
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