Multimodal Self-Supervised Learning for Medical Image Analysis
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Tassilo Klein | Christoph Lippert | Moin Nabi | Aiham Taleb | C. Lippert | T. Klein | Moin Nabi | Aiham Taleb
[1] Hamid R. Rabiee,et al. Puzzle-AE: Novelty Detection in Images through Solving Puzzles , 2020, ArXiv.
[2] Gözde B. Ünal,et al. Deshufflegan: A Self-Supervised Gan to Improve Structure Learning , 2020, 2020 IEEE International Conference on Image Processing (ICIP).
[3] C. Lippert,et al. 3D Self-Supervised Methods for Medical Imaging , 2020, NeurIPS.
[4] Weiming Dong,et al. Self-Supervised Feature Augmentation for Large Image Object Detection , 2020, IEEE Transactions on Image Processing.
[5] Mohammad Havaei,et al. Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders , 2020, ArXiv.
[6] J. Alison Noble,et al. Self-Supervised Representation Learning for Ultrasound Video , 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).
[7] Geoffrey E. Hinton,et al. A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.
[8] Euijoon Ahn,et al. Unsupervised Domain Adaptation to Classify Medical Images Using Zero-Bias Convolutional Auto-Encoders and Context-Based Feature Augmentation , 2020, IEEE Transactions on Medical Imaging.
[9] Xiaowei Ding,et al. Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , 2019, Medical Image Anal..
[10] Ali Razavi,et al. Data-Efficient Image Recognition with Contrastive Predictive Coding , 2019, ICML.
[11] David Dagan Feng,et al. Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer , 2018, IEEE Transactions on Medical Imaging.
[12] Bin Yang,et al. MedGAN: Medical Image Translation using GANs , 2018, Comput. Medical Imaging Graph..
[13] Ke Yan,et al. Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks , 2019, Scientific Reports.
[14] Jiawei Wang,et al. The Retrieval of the Beautiful: Self-Supervised Salient Object Detection for Beauty Product Retrieval , 2019, ACM Multimedia.
[15] Mohan S. Kankanhalli,et al. Self-supervised Representation Learning Using 360° Data , 2019, ACM Multimedia.
[16] Yujiu Yang,et al. Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube , 2019, MICCAI.
[17] Alexei A. Efros,et al. Unsupervised Domain Adaptation through Self-Supervision , 2019, ArXiv.
[18] Nima Tajbakhsh,et al. Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis , 2019, MICCAI.
[19] Abhinav Gupta,et al. Scaling and Benchmarking Self-Supervised Visual Representation Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[20] Fabio Maria Carlucci,et al. Domain Generalization by Solving Jigsaw Puzzles , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Stefano Ermon,et al. Stochastic Optimization of Sorting Networks via Continuous Relaxations , 2019, ICLR.
[22] Ronald M. Summers,et al. A large annotated medical image dataset for the development and evaluation of segmentation algorithms , 2019, ArXiv.
[23] Nima Tajbakhsh,et al. Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data , 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).
[24] Yuxing Tang,et al. XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation , 2018, MIDL.
[25] Mert R. Sabuncu,et al. VoxelMorph: A Learning Framework for Deformable Medical Image Registration , 2018, IEEE Transactions on Medical Imaging.
[26] Euijoon Ahn,et al. Sparsity-based Convolutional Kernel Network for Unsupervised Medical Image Analysis , 2018, Medical image analysis.
[27] Ronald M. Summers,et al. Deep Lesion Graph in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database , 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.
[28] Louis-Philippe Morency,et al. Multimodal Machine Learning: A Survey and Taxonomy , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] Kyomin Jung,et al. Multimodal Speech Emotion Recognition Using Audio and Text , 2018, 2018 IEEE Spoken Language Technology Workshop (SLT).
[30] Björn Ommer,et al. Cross and Learn: Cross-Modal Self-Supervision , 2018, GCPR.
[31] Antonio Albiol,et al. Extending 2D Deep Learning Architectures to 3D Image Segmentation Problems , 2018, BrainLes@MICCAI.
[32] Mauricio Reyes,et al. Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction , 2018, BrainLes@MICCAI.
[33] Klaus H. Maier-Hein,et al. No New-Net , 2018, 1809.10483.
[34] Aaron Carass,et al. Unpaired Brain MR-to-CT Synthesis Using a Structure-Constrained CycleGAN , 2018, DLMIA/ML-CDS@MICCAI.
[35] David Picard,et al. Image Reassembly Combining Deep Learning and Shortest Path Problem , 2018, ECCV.
[36] James R. Glass,et al. Detecting Depression with Audio/Text Sequence Modeling of Interviews , 2018, INTERSPEECH.
[37] Andrew Zisserman,et al. Emotion Recognition in Speech using Cross-Modal Transfer in the Wild , 2018, ACM Multimedia.
[38] Matthijs Douze,et al. Deep Clustering for Unsupervised Learning of Visual Features , 2018, ECCV.
[39] Oriol Vinyals,et al. Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.
[40] Russell H. Taylor,et al. Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy , 2018, OR 2.0/CARE/CLIP/ISIC@MICCAI.
[41] Timo Dickscheid,et al. Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks , 2018, MICCAI.
[42] Andrew Owens,et al. Audio-Visual Scene Analysis with Self-Supervised Multisensory Features , 2018, ECCV.
[43] Ben Glocker,et al. Multi-modal Learning from Unpaired Images: Application to Multi-organ Segmentation in CT and MRI , 2018, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).
[44] Lin Yang,et al. Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[45] Nikos Komodakis,et al. Unsupervised Representation Learning by Predicting Image Rotations , 2018, ICLR.
[46] Scott W. Linderman,et al. Learning Latent Permutations with Gumbel-Sinkhorn Networks , 2018, ICLR.
[47] Edward J. Delp,et al. Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[48] Yong Fan,et al. Non-rigid image registration using self-supervised fully convolutional networks without training data , 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).
[49] Andrew Owens,et al. Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning , 2017, International Journal of Computer Vision.
[50] Antonio Torralba,et al. Cross-Modal Scene Networks , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[51] Christos Davatzikos,et al. Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features , 2017, Scientific Data.
[52] Jelmer M. Wolterink,et al. Deep MR to CT Synthesis Using Unpaired Data , 2017, SASHIMI@MICCAI.
[53] Andrew Zisserman,et al. Self-supervised Learning for Spinal MRIs , 2017, DLMIA/ML-CDS@MICCAI.
[54] Jaakko Lehtinen,et al. Audio-driven facial animation by joint end-to-end learning of pose and emotion , 2017, ACM Trans. Graph..
[55] Andrew Zisserman,et al. Look, Listen and Learn , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[56] Yefeng Zheng,et al. Self supervised deep representation learning for fine-grained body part recognition , 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).
[57] Anoop Cherian,et al. DeepPermNet: Visual Permutation Learning , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[58] Ping Tan,et al. DualGAN: Unsupervised Dual Learning for Image-to-Image Translation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[59] Alexei A. Efros,et al. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[60] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[61] Joon Son Chung,et al. Lip Reading Sentences in the Wild , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[62] Georg Langs,et al. Annotating Medical Image Data , 2017, Cloud-Based Benchmarking of Medical Image Analysis.
[63] Antonio Torralba,et al. SoundNet: Learning Sound Representations from Unlabeled Video , 2016, NIPS.
[64] Abhinav Gupta,et al. Pose from Action: Unsupervised Learning of Pose Features based on Motion , 2016, ArXiv.
[65] David B. Cooper,et al. Solving Small-Piece Jigsaw Puzzles by Growing Consensus , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[66] Bernt Schiele,et al. Generative Adversarial Text to Image Synthesis , 2016, ICML.
[67] Chuan Li,et al. Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks , 2016, ECCV.
[68] Paolo Favaro,et al. Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles , 2016, ECCV.
[69] Alexei A. Efros,et al. Colorful Image Colorization , 2016, ECCV.
[70] Li Fei-Fei,et al. Perceptual Losses for Real-Time Style Transfer and Super-Resolution , 2016, ECCV.
[71] Li Fei-Fei,et al. DenseCap: Fully Convolutional Localization Networks for Dense Captioning , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[72] James R. Glass,et al. Unsupervised Learning of Spoken Language with Visual Context , 2016, NIPS.
[73] Brian B. Avants,et al. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) , 2015, IEEE Transactions on Medical Imaging.
[74] Alexei A. Efros,et al. Unsupervised Visual Representation Learning by Context Prediction , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[75] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[76] Margaret Mitchell,et al. VQA: Visual Question Answering , 2015, International Journal of Computer Vision.
[77] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[78] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[79] David B. Cooper,et al. Solving Square Jigsaw Puzzles with Loop Constraints , 2014, ECCV.
[80] Nathan S. Netanyahu,et al. A Generalized Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles of Complex Types , 2014, AAAI.
[81] Andrew Zisserman,et al. Two-Stream Convolutional Networks for Action Recognition in Videos , 2014, NIPS.
[82] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[83] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[84] D. Kong,et al. Automatic Classification of Early Parkinson's Disease with Multi-Modal MR Imaging , 2012, PloS one.
[85] Andrew C. Gallagher. Jigsaw puzzles with pieces of unknown orientation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[86] Connie Chang. A Patient’s Guide to Medical Imaging , 2011 .
[87] Juhan Nam,et al. Multimodal Deep Learning , 2011, ICML.
[88] Ryan P. Adams,et al. Ranking via Sinkhorn Propagation , 2011, ArXiv.
[89] William T. Freeman,et al. A probabilistic image jigsaw puzzle solver , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[90] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[91] Richard Sinkhorn. A Relationship Between Arbitrary Positive Matrices and Doubly Stochastic Matrices , 1964 .