


default search action
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 Çimen, 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

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.


Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID














