Extended abstracts

The accepted extended abstracts have been gathered in an arXiv compendium: arXiv:1907.08612.

Poster presentations

  • Sequential Rib Labeling and Segmentation in Chest X-Ray Using Mask R-CNN. Joeran Wessel, Mattias P. Heinrich, Jens von Berg, Astrid Franz, Axel Saalbach.
  • Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection. David Zimmerer, Jens Petersen, Fabian Isensee, Klaus Maier-Hein.
  • Multitask Classification and Segmentation for Cancer Diagnosis in Mammography. Thi-Lam-Thuy Le, Nicolas Thome, Sylvain Bernard, Vincent Bismuth, Fanny Patoureaux.
  • Distance Map Loss Penalty Term for Semantic Segmentation. Francesco Caliva, Claudia Iriondo, Alejandro Morales Martinez, Sharmila Majumdar, Valentina Pedoia.
  • Asymmetric Cascade Networks for Focal Bone Lesion Prediction in Multiple Myeloma. Roxane Licandro, Johannes Hofmanninger, Matthias Perkonigg, Sebastian Röhrich, Marc-André Weber, Markus Wennmann, Laurent Kintzele, Marie Piraud, Bjoern Menze, Georg Langs.
  • Combining 3D U-Net and Bottom-up Geometric Constraints for Automatic Cortical Sulci Recognition. Léonie Borne, Denis Rivière, Jean-François Mangin.
  • Applying Simultaneous Super-resolution and Contrast Synthesis to Routine Clinical Magnetic Resonance Images for Automated Segmentation of Knee Joint Cartilage. Ales Neubert, Pierrick Bourgeat, Jason Wood, Craig Engstrom, Shekhar S. Chandra, Stuart Crozier, Jurgen Fripp.
  • Interpretable Convolutional Neural Networks for Preterm Birth Classification. Irina Grigorescu, Lucilio Cordero-Grande, A David Edwards, Jo Hajnal, Marc Modat, Maria Deprez.
  • Towards End-to-End Image-to-Tree for Vasculature Modeling. Manish Sharma, Matthew C. H. Lee, James Batten, Michiel Schaap, Ben Glocker.
  • Deep Learning for Magnetic Resonance Fingerprinting. Solene Girardeau, Ilkay Oksuz, Gastao Cruz, Claudia Pietro Vasquez, Andrew King, James Clough.
  • Cortical Parcellation Via Spectral Graph Convolutions. Karthik Gopinath, Christian Desrosiers, Herve Lombaert.
  • From Point Annotations to Epithelial Cell Detection in Breast Cancer Histopathology Using RetinaNet. Caner Mercan, Maschenka Balkenhol, Jeroen van der Laak, Francesco Ciompi.
  • Improving Localization-based Approaches for Breast Cancer Screening Exam Classification. Thibault Févry, Jason Phang, Nan Wu, S. Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras.
  • HyperDense-Net: A Hyper-densely Connected CNN for Multi-modal Image Segmentation. Jose Dolz, Karthik Gopinath, Jing Yuan, Herve Lombaert, Christian Desrosiers, Ismail Ben Ayed.
  • Deep Learning Segmentation in 2D Echocardiography Using the CAMUS Dataset: Automatic Assessment of the Anatomical Shape Validity. Sarah Leclerc, Erik Smistad, Andreas Ostvik, Frederic Cervenansky, Florian Espinosa, Torvald Espeland, Erik Andreas Rye Berg, Pierre-Marc Jodoin, Thomas Grenier, Carole Lartizien, Lasse Lovstakken, Olivier Bernard.
  • MammoGAN: High-Resolution Synthesis of Realistic Mammograms. Dimitrios Korkinof, Andreas Heindl, Tobias Rijken, Hugh Harvey, Ben Glocker.
  • Forensic Age Estimation With Bayesian Convolutional Neural Networks Based on Panoramic Dental X-ray Imaging. Walter de Back, Sebastian Seurig, Sebastian Wagner, Birgit Marré, Ingo Roeder, Nico Scherf.
  • Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior. Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier.
  • Metric Learning for Patch Classification in Digital Pathology. Eu Wern Teh, Graham W. Taylor.
  • Pulmonary Edema Severity Estimation in Chest Radiographs Using Deep Learning. Xin Wang, Evan Schwab, Jonathan Rubin, Prescott Klassen, Ruizhi Liao, Seth Berkowitz, Polina Golland, Steven Horng, Sandeep Dalal.
  • Automated Interpretation of Prenatal Ultrasound Using a Predefined Acquisition Protocol in Resource-limited Countries. Thomas L. A. van den Heuvel, Chris L. de Korte, Bram van Ginneken.
  • Integrating Spatial Configuration Into Heatmap Regression Based CNNs for Landmark Localization. Christian Payer, Darko Štern, Horst Bischof, Martin Urschler.
  • Total Knee Replacement Prediction Using Structural MRIs and 3D Convolutional Neural Networks. Tianyu Wang, Kevin Leung, Kyunghyun Cho, Gregory Chang, Cem M. Deniz.
  • Automatic Prostate and Prostate Zones Segmentation of Magnetic Resonance Images Using Convolutional Neural Networks. Nader Aldoj, Federico Biavati, Miriam Rutz, Florian Michallek, Sebastian Stober, Marc Dewey.
  • CT Field of View Extension Using Combined Channels Extension and Deep Learning Methods. Éric Fournié, Matthias Baer-Beck, Karl Stierstorfer.
  • Dealing With Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification. Koen Dercksen, Wouter Bulten, Geert Litjens.
  • Automated Segmentation of Left Ventricle in 2D Echocardiography Using Deep Learning. Neda Azarmehr, Xujiong Ye, Faraz Janan, James P Howard, Darrel P Francis, Massoud Zolgharni.
  • Cardio-pulmonary Substructure Segmentation of CT Images Using Convolutional Neural Networks for Clinical Outcome Analysis. Rabia Haq, Alexandra Hotca, Aditya Apte, Andreas Rimner, Joseph O Deasy, Maria Thor.
  • Caveats in Generating Medical Imaging Labels From Radiology Reports With Natural Language Processing. Tobi Olatunji, Li Yao, Ben Covington, Anthony Upton.
  • MR Image Reconstruction Using Deep Density Priors. Kerem C. Tezcan, Christian F. Baumgartner, Roger Luechinger, Klaas P. Pruessmann, Ender Konukoglu.
  • A Closer Look Onto Breast Density With Weakly Supervised Dense-tissue Masks. Mickael Tardy, Bruno Scheffer, Diana Mateus.
  • Odontogenic Cysts and Tumors Detection in Panoramic Radiographs Using Deep Convolutional Neural Network (DCNN). Tae-Hoon Yong, Sang-Jeong Lee, Won-Jin Yi.
  • Fully Automatic Binary Glioma Grading Based on Pre-Therapy MRI Using 3D Convolutional Neural Networks. Milan Decuyper, Roel Van Holen.
  • Machine Learning With Electroencephalography Features for Precise Diagnosis of Depression Subtypes. Maria Zelenina, Diana Maria Pinto Prata.
  • FRODO: Free Rejection of Out-of-distribution Samples: Application to Chest X-ray Analysis. Erdi Çallı, Keelin Murphy, Ecem Sogancioglu, Bram van Ginneken.
  • Colorectal Polyp Size Classification Using a Siamese Network. Benjamin Villard, Yuichi Mori, Masashi Misawa, Shin-ei Kudo, Hayato Itoh, Masahiro Oda, Kensaku Mori.
  • Deep Convolution Neural Network Model for Automatic Risk Assessment of Patients With Non-metastatic Nasopharyngeal Carcinoma. Richard Du, Peng Cao, Lujun Han, Qiyong Ai, Ann D. King, Varut Vardhanabhuti.
  • Brain Tumor Segmentation Using Topological Loss in Convolutional Networks. Charan Reddy, Karthik Gopinath, Herve Lombaert.
  • Significance of Residual Learning and Boundary Weighted Loss in Ischaemic Stroke Lesion Segmentation. Ronnie Rajan, Rachana Sathish, Debdoot Sheet.
  • Stratify or Inject: Two Simple Training Strategies to Improve Brain Tumor Segmentation. Raphael Meier, Michael Rebsamen, Urspeter Knecht, Mauricio Reyes, Roland Wiest, Richard McKinley.
  • Efficient Neural Architecture Search on Low-Dimensional Data for OCT Image Segmentation. Nils Gessert, Alexander Schlaefer.
  • Guiding 3D U-Nets With Signed Distance Fields for Creating 3D Models From Images. Kristine Aavild Juhl, Rasmus Reinhold Paulsen, Anders Bjorholm Dahl, Vedrana Andersen Dahl, Ole De Backer, Klaus Fuglsang Kofoed, Oscar Camara.
  • Biasing Deep ConvNets for Semantic Segmentation of Medical Images With a Prior-driven Prediction Function. Olivier Petit, Nicolas Thome, Luc Soler.
  • Chest CT Super-resolution and Domain-adaptation Using Memory-efficient 3D Reversible GANs. Tycho F.A. van der Ouderaa, Daniel E. Worrall, Bram van Ginneken.
  • Sparse Annotations With Random Walks for U-Net Segmentation of Biodegradable Bone Implants in Synchrotron Microtomograms. Niclas Bockelmann, Diana Krüger, D.C. Florian Wieland, Berit Zeller-Plumhoff, Niccoló Peruzzi, Silvia Galli, Regine Willumeit-Römer, Fabian Wilde, Felix Beckmann, Jörg Hammel, Julian Moosmann, Mattias P. Heinrich.
  • Synthetic CT Generation From MRI Using Improved DualGAN. Denis Prokopenko, Joël Valentin Stadelmann, Heinrich Schulz, Steffen Renisch, Dmitry V. Dylov.
  • Deep Fully Convolutional Network for MR Fingerprinting. Dongdong Chen, Mohammad Golbabaee, Pedro A Gómez, Marion I Menzel, Mike E Davies.
  • A Generalized Network for MRI Intensity Normalization. Attila Simkó, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Joakim Jonsson.
  • Deep Learning Based Partial Annotation Framework for Instance Segmentation in Histopathology Images. Elad Arbel, Itay Remer, Amir Ben-Dor.
  • Hepatic Vessel Segmentation Using a Reduced Filter 3D U-Net in Ultrasound Imaging. Bart R. Thomson, Jasper Nijkamp, Oleksandra Ivashchenko, Ferdinand van der Heijden, Jasper N. Smit, Niels F.M. Kok, Koert F.D. Kuhlmann, Theo J.M. Ruers, Matteo Fusaglia.
  • Robustly Segmenting Quadriceps Muscles of Ultra-endurance Athletes With Weakly Supervised U-Net. Hoai-Thu Nguyen, Pierre Croisille, Magalie Viallon, Sarah Leclerc, Sylvain Grange, Rémi Grange, Olivier Bernard, Thomas Grenier.
  • Coronary Artery Segmentation in Cardiac CT Angiography Using 3D Multi-Channel U-Net. Yo-Chuan Chen, Yi-Chen Lin, Ching-Ping Wang, Chia-Yen Lee, Tzung-Dau Wang, Wen-Jeng Lee, Chung-Ming Chen.
  • Effect of Adding Probabilistic Zonal Prior in Deep Learning-based Prostate Cancer Detection. Matin Hosseinzadeh, Patrick Brand, Henkjan Huisman.
  • Regression Activation Mapping on the Cortical Surface Using Graph Convolutional Networks. Ben A Duffy, Mengting Liu, Trevor Flynn, Arthur W Toga, A. James Barkovich, Duan Xu, Hosung Kim.
  • Synthesis of CT Images Using CycleGANs: Enhancement of Anatomical Accuracy. Dominik F. Bauer, Alena-Kathrin Schnurr, Tom Russ, Stephan Goerttler, Lothar R. Schad, Frank G. Zoellner, Khanlian Chung.
  • Spatio-temporal Regularization for Deep MR Fingerprinting. Mohammad Golbabaee, Dongdong Chen, Mike Davies, Marion I. Menzel, Pedro A. Gomez.
  • Deep Posterior Sampling: Uncertainty Quantification for Large Scale Inverse Problems. Jonas Adler, Ozan Öktem.
  • Is Texture Predictive for Age and Sex in Brain MRI?. Nick Pawlowski, Ben Glocker.
  • Vertebra Partitioning With Thin-plate Spline Surfaces Steered by a Convolutional Neural Network. Nikolas Lessmann, Jelmer M. Wolterink, Majd Zreik, Max A. Viergever, Bram van Ginneken, Ivana Išgum.
  • GANs ’N Lungs: Improving Pneumonia Prediction. Tatiana Malygina, Elena Ericheva, Ivan Drokin.
  • Simultaneous Detection and Grading of Prostate Cancer in Multi-Parametric MRI. Coen de Vente, Pieter Vos, Josien Pluim, Mitko Veta.
  • Screening Mammogram Classification With Prior Exams. Jungkyu Park, Jason Phang, Yiqiu Shen, Nan Wu, S. Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras.
  • Optimal Windowing of MR Images Using Deep Learning: An Enabler for Enhanced Visualization. Deepthi Sundaran, Dheeraj Kulkarni, Jignesh Dholakia.
  • Pneumothorax Detection and Localization in Chest Radiographs: A Comparison of Deep Learning Approaches. André Gooßen, Hrishikesh Deshpande, Tim Harder, Evan Schwab, Ivo Baltruschat, Thusitha Mabotuwana, Nathan Cross, Axel Saalbach.
  • Pathological Myopic Image Analysis With Transfer Learning. Ruitao Xie, Libo Liu, Jingxin Liu, Connor S Qiu.
  • Geometric Deep Learning and Heatmap Prediction for Large Deformation Registration of Abdominal and Thoracic CT. In Young Ha, Lasse Hansen, Matthias Wilms, Mattias P. Heinrich.
  • A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging. Li Yao, Jordan Prosky, Ben Covington, Kevin Lyman.
  • GradMask: Reduce Overfitting by Regularizing Saliency. Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen.
  • Tumor Semantic Segmentation in Hyperspectral Images Using Deep Learning. Stojan Trajanovski, Caifeng Shan, Pim J. C. Weijtmans, Susan G. Brouwer de Koning, Theo J. M. Ruers.
  • Modeling Clinical Assessor Intervariability Using Deep Hypersphere Auto-encoders. Joost van der Putten, Fons van der Sommen, Jeroen de Groof, Maarten Struyvenberg, Svitlana Zinger, Wouter Curvers, Erik Schoon, Jaques Bergman, Peter H.N. de With.
  • Using Collaged Data Augmentation to Train Deep Neural Net With Few Data. Hsun-An Chiang, Cheng-Shao Chiang, Chi-Sheng Shih.
  • Prostate Cancer Segmentation Using Manifold Mixup U-Net. Wonmo Jung, Sejin Park, Kyu-Hwan Jung, Sung Il Hwang.
  • Extended 2D Consensus Hippocampus Segmentation. Diedre Carmo, Bruna Silva, Clarissa Yasuda, Leticia Rittner, Roberto Lotufo.
  • Uncertainty-Driven Semantic Segmentation Through Human-Machine Collaborative Learning. Mahdyar Ravanbakhsh, Tassilo Klein, Kayhan Batmanghelich, Moin Nabi.
  • A Multi-Task Self-Normalizing 3D-CNN to Infer Tuberculosis Radiological Manifestations. Pedro M. Gordaliza, Juan José Vaquero, Sally Sharpe, Fergus Gleeson, Arrate Muñoz-Barrutia.
  • Relevance Analysis of MRI Sequences for Automatic Liver Tumor Segmentation. Grzegorz Chlebus, Nasreddin Abolmaali, Andrea Schenk, Hans Meine.
  • Efficient Prealignment of CT Scans for Registration Through a Bodypart Regressor. Hans Meine, Alessa Hering.
  • Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model Say “I Don’t Know“ for Ambiguous Cases. Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier.
  • Low Dose SPECT Image Denoising Using a Generative Adversarial Network. Qi Zhang, Jingzhang Sun, Greta S. P. Mok.
  • Towards Manifold Learning of Image-Based Motion Models for Oscillating Vocal Folds. Sontje Ihler, Max-Heinrich Laves, Tobias Ortmaier.
  • Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results. Alex E. Bocchieri, Vishwa S. Parekh, Kathryn R. Wagner, Shivani Ahlawat, Vladimir Braverman, Doris G. Leung, Michael A. Jacobs.
  • Template Transformer Networks for Image Segmentation. Matthew Chung Hai Lee, Kersten Petersen, Nick Pawlowski, Ben Glocker, Michiel Schaap.
  • Machine Learning of Multimodal MRI to Predict the Development of Epileptic Seizures After Traumatic Brain Injury. Marianna La Rocca, Rachael Garner, Kay Jann, Hosung Kim, Paul Vespa, Arthur W Toga, Dominique Duncan.
  • BACH: Grand Challenge on Breast Cancer Histology Images. Guilherme Aresta, Teresa Araújo, Aurélio Campilho, Catarina Eloy, António Polónia, Paulo Aguiar.
  • Major Vessel Segmentation on X-ray Coronary Angiography Using Deep Networks With a Novel Penalty Loss Function. Su Yang, Jihoon Kweon, Young-Hak Kim.
  • CNN-Based Segmentation of the Cardiac Chambers and Great Vessels in Non-Contrast-Enhanced Cardiac CT. Steffen Bruns, Jelmer M. Wolterink, Robbert W. van Hamersvelt, Tim Leiner, Ivana Išgum.
  • On the Effects of Vendor Balancing in Deep Learning for Mammography. Edwin D. de Jong, Jaap Kroes.
  • Transfer Learning From Synthetic Data Reduces Need for Labels to Segment Brain Vasculature and Neural Pathways in 3D. Johannes C. Paetzold, Oliver Schoppe, Rami Al-Maskari, Giles Tetteh, Velizar Efremov, Mihail I. Todorov, Ruiyao Cai, Hongcheng Mai, Zhouyi Rong, Ali Ertuerk, Bjoern H. Menze.
  • Deep Learning for Automatic Tumour Segmentation in PET/CT Images of Patients With Head and Neck Cancers. Yngve Mardal Moe, Aurora Rosvoll Groendahl, Martine Mulstad, Oliver Tomic, Ulf Indahl, Einar Dale, Eirik Malinen, Cecilia Marie Futsaether.
  • 4D Spatio-Temporal Deep Learning With 4D FMRI Data for Autism Spectrum Disorder Classification. Marcel Bengs, Nils Gessert, Alexander Schlaefer.
  • Uncertainty Handling in Intra-operative Multispectral Imaging With Invertible Neural Networks. Tim J. Adler, Lynton Ardizzone, Leonardo Ayala, Janek Gröhl, Anant Vemuri, Sebastian J. Wirkert, Beat P. Müller-Stich, Carsten Rother, Ullrich Köthe, Lena Maier-Hein.
  • Deep Learning-based Prediction of Kinetic Parameters From Myocardial Perfusion MRI. Cian M. Scannell, Piet van den Bosch, Amedeo Chiribiri, Jack Lee, Marcel Breeuwer, Mitko Veta.
  • Do Lateral Views Help Automated Chest X-ray Predictions?. Hadrien Bertrand, Mohammad Hashir, Joseph Paul Cohen.
  • Deep Neural Networks for Quality Assurance of Image Registration. Sarah Bannister, Denis Page, Thomas Standen, Alexander Dunne, Jacob Rawling, Callum Jacob Birch-Sykes, Megan Z Wilson, Stacey Holloway, Jamie R. McClelland, Yvonne Peters.
  • Automated Mammogram Analysis With a Deep Learning Pipeline. Azam Hamidinekoo, Erika Denton, Reyer Zwiggelaar.
  • Multiscale Deep Neural Networks for Multiclass Tissue Classification of Histological Whole-Slide Images. Rune Wetteland, Kjersti Engan, Trygve Eftestøl, Vebjørn Kvikstad, Emilius A.M. Janssen.
  • Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening. Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanisław Jastrzębski, Thibault Févry, Joe Katsnelson, Eric Kim, Stacey Wolfson, Ujas Parikh, Sushma Gaddam, Leng Leng Young Lin, Joshua D. Weinstein, Krystal Airola, Eralda Mema, Stephanie Chung, Esther Hwang, Naziya Samreen, Kara Ho, Beatriu Reig, Yiming Gao, Hildegard Toth, Kristine Pysarenko, Alana Lewin, Jiyon Lee, Laura Heacock, S. Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras.
  • Conditional Networks for Screening of Breast Cancer Metastases in Lymph Nodes. Gianluca Gerard, Marco Piastra.
  • Robust Reconstruction of Cardiac T1 Maps Using RNNs. Nicola Martini, Alessio Vatti, Andrea Ripoli, Sara Salaris, Gianmarco Santini, Gabriele Valvano, Maria Filomena Santarelli, Dante Chiappino, Daniele Della Latta.
  • Shadow Detection for Ultrasound Images Using Unlabeled Data and Synthetic Shadows. Suguru Yasutomi, Tatsuya Arakaki, Ryuji Hamamoto.
  • Lung Nodules Detection and Segmentation Using 3D Mask-RCNN. Evi Kopelowitz, Guy Englehard.
  • Conditioning Convolutional Segmentation Architectures With Non-Imaging Data. Grzegorz Jacenków, Agisilaos Chartsias, Brian Mohr, Sotirios A. Tsaftaris.
  • Towards Continuous Learning for Glioma Segmentation With Elastic Weight Consolidation. Karin van Garderen, Sebastian van der Voort, Fatih Incekara, Marion Smits, Stefan Klein.