MIDL 2019 Conference Abstract Submissions

Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say “I don’t know“ for Ambiguous Cases
Max-Heinrich Laves, Sontje Ihler, Tobias Ortmaier
- 18 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Conditioning Convolutional Segmentation Architectures with Non-Imaging Data
Grzegorz Jacenków, Agisilaos Chartsias, Brian Mohr, Sotirios A. Tsaftaris
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Significance of Residual Learning and Boundary Weighted Loss in Ischaemic Stroke Lesion Segmentation
Ronnie Rajan, Rachana Sathish, Debdoot Sheet
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Uncertainty-Driven Semantic Segmentation through Human-Machine Collaborative Learning
Mahdyar Ravanbakhsh, Tassilo Klein, Kayhan Batmanghelich, Moin Nabi
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Biasing Deep ConvNets for Semantic Segmentation of Medical Images with a Prior-driven Prediction Function
Olivier Petit, Nicolas Thome, Luc Soler
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification
Koen Dercksen, Wouter Bulten, Geert Litjens
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Towards continuous learning for glioma segmentation with elastic weight consolidation
Karin van Garderen, Sebastian van der Voort, Fatih Incekara, Marion Smits, Stefan Klein
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
MammoGAN: High-Resolution Synthesis of Realistic Mammograms
Dimitrios Korkinof, Andreas Heindl, Tobias Rijken, Hugh Harvey, Ben Glocker
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Deep Learning Based Partial Annotation Framework for Instance Segmentation in Histopathology Images
Elad Arbel, Itay Remer, Amir Ben-Dor
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
CT Field of View Extension Using Combined Channels Extension and Deep Learning Methods
Éric Fournié, Matthias Baer-Beck, Karl Stierstorfer
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Interpretable Convolutional Neural Networks for Preterm Birth Classification
Irina Grigorescu, Lucilio Cordero-Grande, A David Edwards, Jo Hajnal, Marc Modat, Maria Deprez
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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,
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
4D Spatio-Temporal Deep Learning with 4D fMRI Data for Autism Spectrum Disorder Classification
Marcel Bengs, Nils Gessert, Alexander Schlaefer
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Towards Manifold Learning of Image-Based Motion Models for Oscillating Vocal Folds
Sontje Ihler, Max-Heinrich Laves, Tobias Ortmaier
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Colorectal Polyp Size Classification Using a Siamese Network
Benjamin Villard, Yuichi Mori, Masashi Misawa, Shin-ei Kudo, Hayato Itoh, Masahiro Oda, Kensaku Mori
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Effect of Adding Probabilistic Zonal Prior in Deep Learning-based Prostate Cancer Detection
Matin Hosseinzadeh, Patrick Brand, Henkjan Huisman
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
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
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Deep posterior sampling: Uncertainty quantification for large scale inverse problems
Jonas Adler, Ozan Öktem
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone
Prostate Cancer Segmentation using Manifold Mixup U-Net
Wonmo Jung, Sejin Park, Kyu-Hwan Jung, Sung Il Hwang
- 17 Apr 2019 (modified: 05 May 2023)
- MIDL Abstract 2019
- Readers: Everyone