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MIDL 2019: London, UK
- M. Jorge Cardoso, Aasa Feragen, Ben Glocker, Ender Konukoglu, Ipek Oguz, Gozde B. Unal, Tom Vercauteren:
International Conference on Medical Imaging with Deep Learning, MIDL 2019, 8-10 July 2019, London, United Kingdom. Proceedings of Machine Learning Research 102, PMLR 2019
Preface
- Preface. 1-3
Contributed Papers
- Amir H. Abdi, Heather Borgard, Purang Abolmaesumi, Sidney S. Fels:
AnatomyGen: Deep Anatomy Generation From Dense Representation With Applications in Mandible Synthesis. 4-14 - Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet, Adrien Depeursinge:
Exploring local rotation invariance in 3D CNNs with steerable filters. 15-26 - Fabian Balsiger, Olivier Scheidegger, Pierre G. Carlier, Benjamin Marty, Mauricio Reyes:
On the Spatial and Temporal Influence for the Reconstruction of Magnetic Resonance Fingerprinting. 27-38 - Cher Bass, Tianhong Dai, Benjamin Billot, Kai Arulkumaran, Antonia Creswell, Claudia Clopath, Vincenzo De Paola, Anil Anthony Bharath:
Image Synthesis with a Convolutional Capsule Generative Adversarial Network. 39-62 - Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Fusing Unsupervised and Supervised Deep Learning for White Matter Lesion Segmentation. 63-72 - Max Blendowski, Mattias P. Heinrich:
Learning interpretable multi-modal features for alignment with supervised iterative descent. 73-83 - John-Melle Bokhorst, Hans Pinckaers, Peter van Zwam, Iris Nagtegaal, Jeroen van der Laak, Francesco Ciompi:
Learning from sparsely annotated data for semantic segmentation in histopathology images. 84-91 - Nikolay Burlutskiy, Nicolas Pinchaud, Feng Gu, Daniel Hägg, Mats Andersson, Lars Björk, Kristian Eurén, Cristina Svensson, Lena Kajland Wilén, Martin Hedlund:
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data. 92-108 - Haomin Chen, Shun Miao, Daguang Xu, Gregory D. Hager, Adam P. Harrison:
Deep Hierarchical Multi-label Classification of Chest X-ray Images. 109-120 - Marc Combalia
, Javiera Pérez-Anker, Adriana García-Herrera, Llúcia Alos, Verónica Vilaplana, Ferran Marqués, Susana Puig, Josep Malvehy:
Digitally Stained Confocal Microscopy through Deep Learning. 121-129 - Tianhong Dai, Magda Dubois, Kai Arulkumaran, Jonathan Campbell, Cher Bass, Benjamin Billot, Fatmatülzehra Uslu, Vincenzo De Paola, Claudia Clopath, Anil Anthony Bharath:
Deep Reinforcement Learning for Subpixel Neural Tracking. 130-150 - Thomas de Bel, Meyke Hermsen, Jesper Kers, Jeroen van der Laak, Geert Litjens:
Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology. 151-163 - Reuben Dorent, Wenqi Li, Jinendra Ekanayake, Sébastien Ourselin, Tom Vercauteren:
Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets. 164-174 - Michael Gadermayr, Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof:
Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations. 175-184 - Robin Geyer, Luca Corinzia, Viktor Wegmayr:
Transfer Learning by Adaptive Merging of Multiple Models. 185-196 - Marc Górriz, Joseph Antony, Kevin McGuinness, Xavier Giró-i-Nieto, Noel E. O'Connor:
Assessing Knee OA Severity with CNN attention-based end-to-end architectures. 197-214 - Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof, Michael Gadermayr:
Iterative learning to make the most of unlabeled and quickly obtained labeled data in histology. 215-224 - Anant Gupta, Srivas Venkatesh, Sumit Chopra, Christian Ledig:
Generative Image Translation for Data Augmentation of Bone Lesion Pathology. 225-235 - Jannis Hagenah, Kenneth Kühl, Michael Scharfschwerdt, Floris Ernst:
Cluster Analysis in Latent Space: Identifying Personalized Aortic Valve Prosthesis Shapes using Deep Representations. 236-249 - Lasse Hansen, Mattias P. Heinrich:
Sparse Structured Prediction for Semantic Edge Detection in Medical Images. 250-259 - Seyed Raein Hashemi, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour:
Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets: Application to IsoIntense Infant Brain MRI Segmentation. 260-272 - Qiaoying Huang, Dong Yang, Hui Qu, Jingru Yi, Pengxiang Wu, Dimitris N. Metaxas:
Dynamic MRI Reconstruction with Motion-Guided Network. 275-284 - Hoel Kervadec
, Jihene Bouchtiba, Christian Desrosiers, Eric Granger, Jose Dolz, Ismail Ben Ayed:
Boundary loss for highly unbalanced segmentation. 285-296 - Seyed Mostafa Kia, Andre F. Marquand:
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data. 297-314 - Maxime W. Lafarge, Juan C. Caicedo, Anne E. Carpenter, Josien P. W. Pluim, Shantanu Singh, Mitko Veta:
Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning. 315-325 - Kyungmoon Lee, Min-Kook Choi, Heechul Jung:
DavinciGAN: Unpaired Surgical Instrument Translation for Data Augmentation. 326-336 - Bart Liefers, Cristina González-Gonzalo, Caroline Klaver, Bram van Ginneken, Clara I. Sánchez:
Dense Segmentation in Selected Dimensions: Application to Retinal Optical Coherence Tomography. 337-346 - Tanja Lossau, Hannes Nickisch, Tobias Wissel, Samer Hakmi, Clemens Spink, Michael M. Morlock, Michael Grass:
Dynamic Pacemaker Artifact Removal (DyPAR) from CT Data using CNNs. 347-357 - Jiechao Ma, Xiang Li, Hongwei Li
, Bjoern H. Menze, Sen Liang, Rongguo Zhang, Wei-Shi Zheng:
Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images. 358-369 - Huu-Giao Nguyen, Alessia Pica, Jan Hrbacek, Damien C. Weber, Francesco La Rosa, Ann Schalenbourg, Raphael Sznitman, Meritxell Bach Cuadra:
A novel segmentation framework for uveal melanoma in magnetic resonance imaging based on class activation maps. 370-379 - Ilkay Öksüz, James R. Clough, Wenjia Bai, Bram Ruijsink, Esther Puyol-Antón, Gastão Cruz, Claudia Prieto, Andrew P. King, Julia A. Schnabel:
High-quality segmentation of low quality cardiac MR images using k-space artefact correction. 380-389 - Hui Qu, Pengxiang Wu, Qiaoying Huang, Jingru Yi, Gregory M. Riedlinger, Subhajyoti De, Dimitris N. Metaxas:
Weakly Supervised Deep Nuclei Segmentation using Points Annotation in Histopathology Images. 390-400 - Nicolas Roulet, Diego Fernández Slezak, Enzo Ferrante:
Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets. 401-413 - Oindrila Saha, Rachana Sathish, Debdoot Sheet:
Learning with Multitask Adversaries using Weakly Labelled Data for Semantic Segmentation in Retinal Images. 414-426 - Richard Shaw, Carole H. Sudre, Sébastien Ourselin, M. Jorge Cardoso:
MRI k-Space Motion Artefact Augmentation: Model Robustness and Task-Specific Uncertainty. 427-436 - Roberto Souza, R. Marc Lebel, Richard Frayne:
A Hybrid, Dual Domain, Cascade of Convolutional Neural Networks for Magnetic Resonance Image Reconstruction. 437-446 - Carole H. Sudre, Beatriz Gomez Anson, Silvia Ingala, Chris D. Lane, Daniel Jimenez, Lukas Haider, Thomas Varsavsky, Lorna Smith, Sébastien Ourselin, Hans Rolf Jäger, M. Jorge Cardoso:
3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects. 447-456 - Youbao Tang, Yuxing Tang, Jing Xiao, Ronald M. Summers:
XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation. 457-467 - Daniel Toth, Serkan Cimen, Pascal Ceccaldi, Tanja Kurzendorfer, Kawal S. Rhode, Peter Mountney:
Training Deep Networks on Domain Randomized Synthetic X-ray Data for Cardiac Interventions. 468-482 - Adrian Tousignant, Paul Lemaître, Doina Precup, Douglas L. Arnold, Tal Arbel:
Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data. 483-492 - Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov, Alexander M. Bronstein, Oleg V. Michailovich, Michael Zibulevsky:
Learning beamforming in ultrasound imaging. 493-511 - Tian Xia, Agisilaos Chartsias, Sotirios A. Tsaftaris:
Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization. 512-526 - Chensu Xie, Chad M. Vanderbilt, Anne Grabenstetter, Thomas J. Fuchs:
VOCA: Cell Nuclei Detection In Histopathology Images By Vector Oriented Confidence Accumulation. 527-539 - Suhang You, Kerem Can Tezcan, Xiaoran Chen, Ender Konukoglu:
Unsupervised Lesion Detection via Image Restoration with a Normative Prior. 540-556 - Farhad Ghazvinian Zanjani, David Anssari Moin, Bas Verheij, Frank Claessen, Teo Cherici, Tao Tan, Peter H. N. de With:
Deep Learning Approach to Semantic Segmentation in 3D Point Cloud Intra-oral Scans of Teeth. 557-571 - Yizhe Zhang, Lin Yang, Hao Zheng, Peixian Liang, Colleen Mangold, Raquel G. Loreto, David P. Hughes, Danny Z. Chen:
SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation. 572-587 - Jiaxin Zhuang
, Jiabin Cai, Ruixuan Wang, Jianguo Zhang, Weishi Zheng:
CARE: Class Attention to Regions of Lesion for Classification on Imbalanced Data. 588-597
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