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MIDL 2020: Montréal, QC, Canada
- Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux, Hervé Lombaert, Christopher Pal:
International Conference on Medical Imaging with Deep Learning, MIDL 2020, 6-8 July 2020, Montréal, QC, Canada. Proceedings of Machine Learning Research 121, PMLR 2020 - Preface. 1-5
- Samaneh Abbasi-Sureshjani, Sina Amirrajab, Cristian Lorenz, Jürgen Weese, Josien P. W. Pluim, Marcel Breeuwer:
4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model. 6-18 - Jakob K. H. Andersen, Jakob Grauslund, Thiusius R. Savarimuthu:
Comparing Objective Functions for Segmentation and Detection of Microaneurysms in Retinal Images. 19-32 - Vincent Andrearczyk, Valentin Oreiller, Martin Vallières, Joël Castelli, Hesham Elhalawani, Mario Jreige, Sarah Boughdad, John O. Prior, Adrien Depeursinge:
Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans. 33-43 - Devanshu Arya, Richard Olij, Deepak K. Gupta, Ahmed El Gazzar, Guido van Wingen, Marcel Worring, Rajat Mani Thomas:
Fusing Structural and Functional MRIs using Graph Convolutional Networks for Autism Classification. 44-61 - Laurens Beljaards, Mohamed S. Elmahdy, Fons J. Verbeek, Marius Staring:
A Cross-Stitch Architecture for Joint Registration and Segmentation in Adaptive Radiotherapy. 62-74 - Benjamin Billot, Douglas N. Greve, Koen Van Leemput, Bruce Fischl, Juan Eugenio Iglesias, Adrian V. Dalca:
A Learning Strategy for Contrast-agnostic MRI Segmentation. 75-93 - Francesco Calivá, Andrew P. Leynes, Rutwik Shah, Upasana Upadhyay Bharadwaj, Sharmila Majumdar, Peder E. Z. Larson, Valentina Pedoia:
Breaking Speed Limits with Simultaneous Ultra-Fast MRI Reconstruction and Tissue Segmentation. 94-110 - Vincent Casser, Kai Kang, Hanspeter Pfister, Daniel Haehn:
Fast Mitochondria Detection for Connectomics. 111-120 - Kaiyang Cheng, Francesco Calivá, Rutwik Shah, Misung Han, Sharmila Majumdar, Valentina Pedoia:
Addressing The False Negative Problem of Deep Learning MRI Reconstruction Models by Adversarial Attacks and Robust Training. 121-135 - Joseph Paul Cohen, Mohammad Hashir, Rupert Brooks, Hadrien Bertrand:
On the limits of cross-domain generalization in automated X-ray prediction. 136-155 - Yukun Ding, Jinglan Liu, Xiaowei Xu, Meiping Huang, Jian Zhuang, Jinjun Xiong, Yiyu Shi:
Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation. 156-173 - Richard Du, Varut Vardhanabhuti:
3D-RADNet: Extracting labels from DICOM metadata for training general medical domain deep 3D convolution neural networks. 174-192 - Audrey Duran, Pierre-Marc Jodoin, Carole Lartizien:
Prostate Cancer Semantic Segmentation by Gleason Score Group in bi-parametric MRI with Self Attention Model on the Peripheral Zone. 193-204 - Pierre Erbacher, Carole Lartizien, Matthieu Martin, Pedro Foletto-Pimenta, Philippe Quetin, Philippe Delachartre:
Priority U-Net: Detection of Punctuate White Matter Lesions in Preterm Neonate in 3D Cranial Ultrasonography. 205-216 - Achraf Essemlali, Etienne St-Onge, Maxime Descoteaux, Pierre-Marc Jodoin:
Understanding Alzheimer disease's structural connectivity through explainable AI. 217-229 - Ahmed E. Fetit, John Cupitt, Turkay Kart, Daniel Rueckert:
Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain. 230-240 - Ahmed E. Fetit, Amir Alansary, Lucilio Cordero-Grande, John Cupitt, Alice B. Davidson, A. David Edwards, Joseph V. Hajnal, Emer J. Hughes, Konstantinos Kamnitsas, Vanessa Kyriakopoulou, Antonios Makropoulos, Prachi A. Patkee, Anthony N. Price, Mary A. Rutherford, Daniel Rueckert:
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling. 241-261 - Logan Gilmour, Nilanjan Ray:
Locating Cephalometric X-Ray Landmarks with Foveated Pyramid Attention. 262-276 - Mohammad MinHazul Haq, Junzhou Huang:
Adversarial Domain Adaptation for Cell Segmentation. 277-287 - Mohammad Hashir, Hadrien Bertrand, Joseph Paul Cohen:
Quantifying the Value of Lateral Views in Deep Learning for Chest X-rays. 288-303 - Peter Hirsch, Dagmar Kainmueller:
An Auxiliary Task for Learning Nuclei Segmentation in 3D Microscopy Images. 304-321 - Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling:
DIVA: Domain Invariant Variational Autoencoders. 322-348 - Padmaja Jonnalagedda, Brent D. Weinberg, Jason Allen, Bir Bhanu:
Feature Disentanglement to Aid Imaging Biomarker Characterization for Genetic Mutations. 349-364 - Hoel Kervadec, Jose Dolz, Shanshan Wang, Eric Granger, Ismail Ben Ayed:
Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision. 365-381 - Zhuo Kuang, Xianbo Deng, Li Yu, Hang Zhang, Xian Lin, Hui Ma:
Skull R-CNN: A CNN-based network for the skull fracture detection. 382-392 - Max-Heinrich Laves, Sontje Ihler, Jacob Friedemann Fast, Lüder A. Kahrs
, Tobias Ortmaier:
Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning. 393-412 - Matthias Lenga, Heinrich Schulz, Axel Saalbach:
Continual Learning for Domain Adaptation in Chest X-ray Classification. 413-423 - Wanyue Li, Wen Kong, Yiwei Chen, Jing Wang, Yi He, Guohua Shi, Guohua Deng:
Generating Fundus Fluorescence Angiography Images from Structure Fundus Images Using Generative Adversarial Networks. 424-439 - Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara:
Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing. 440-453 - Haoyun Liang, Yu Gong, Hoel Kervadec, Cheng Li, Jing Yuan, Xin Liu, Hairong Zheng, Shanshan Wang:
Laplacian pyramid-based complex neural network learning for fast MR imaging. 454-464 - Jasper Linmans, Jeroen van der Laak, Geert Litjens:
Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks. 465-478 - Jun Ma, Zhan Wei, Yiwen Zhang, Yixin Wang, Rongfei Lv, Cheng Zhu, Chen Gaoxiang, Jianan Liu, Chao Peng, Lei Wang, Yunpeng Wang, Jianan Chen:
How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study. 479-492 - Da Ma, Donghuan Lu, Morgan Heisler, Setareh Dabiri, Sieun Lee, Gavin Weiguang Ding, Marinko V. Sarunic, Mirza Faisal Beg:
Cascade Dual-branch Deep Neural Networks for Retinal Layer and fluid Segmentation of Optical Coherence Tomography Incorporating Relative Positional Map. 493-502 - Brandon Mac, Alan R. Moody, April Khademi:
Siamese Content Loss Networks for Highly Imbalanced Medical Image Segmentation. 503-514 - Balamurali Murugesan, Sricharan Vijayarangan, Kaushik Sarveswaran, Keerthi Ram, Mohanasankar Sivaprakasam:
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflow. 515-526 - Abhishek Nan, Matthew Tennant, Uriel Rubin, Nilanjan Ray:
DRMIME: Differentiable Mutual Information and Matrix Exponential for Multi-Resolution Image Registration. 527-543 - Fernando Navarro, Anjany Sekuboyina, Diana Waldmannstetter, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze:
Deep Reinforcement Learning for Organ Localization in CT. 544-554 - Nhat M. Nguyen, Nilanjan Ray:
End-to-end learning of convolutional neural net and dynamic programming for left ventricle segmentation. 555-569 - Andreas Panteli, Deepak K. Gupta, Nathan de Bruijn, Efstratios Gavves:
Siamese Tracking of Cell Behaviour Patterns. 570-587 - Vishwa S. Parekh, Alex E. Bocchieri, Vladimir Braverman, Michael A. Jacobs:
Multitask radiological modality invariant landmark localization using deep reinforcement learning. 588-600 - Jizong Peng, Marco Pedersoli, Christian Desrosiers:
Mutual information deep regularization for semi-supervised segmentation. 601-613 - Cheng Peng, Wei-An Lin, Rama Chellappa, S. Kevin Zhou:
Towards multi-sequence MR image recovery from undersampled k-space data. 614-623 - Georg Pichler, Jose Dolz, Ismail Ben Ayed, Pablo Piantanida:
On Direct Distribution Matching for Adapting Segmentation Networks. 624-637 - Carolin M. Pirkl, Pedro A. Gómez, Ilona Lipp, Guido Buonincontri, Miguel Molina-Romero, Anjany Sekuboyina, Diana Waldmannstetter, Jonathan Dannenberg, Sebastian Endt, Alberto Merola, Joseph R. Whittaker, Valentina Tomassini, Michela Tosetti, Derek K. Jones, Bjoern H. Menze, Marion I. Menzel:
Deep learning-based parameter mapping for joint relaxation and diffusion tensor MR Fingerprinting. 638-654 - Ahmad Bin Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe, Johannes C. Paetzold, Anjany Sekuboyina, Florian Kofler, Jana Lipková, Hongwei Li, Bjoern H. Menze:
Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective. 655-668 - Adalberto Claudio Quiros, Roderick Murray-Smith, Ke Yuan:
PathologyGAN: Learning deep representations of cancer tissue. 669-695 - Sriprabha Ramanarayanan, Balamurali Murugesan, Keerthi Ram, Mohanasankar Sivaprakasam:
MAC-ReconNet: A Multiple Acquisition Context based Convolutional Neural Network for MR Image Reconstruction using Dynamic Weight Prediction. 696-708 - Luisa Sánchez Brea, Danilo Andrade De Jesus, Stefan Klein, Theo van Walsum:
Deep learning-based retinal vessel segmentation with cross-modal evaluation. 709-720 - Raghavendra Selvan, Erik B. Dam:
Tensor Networks for Medical Image Classification. 721-732 - Richard Shaw, Carole H. Sudre, Sébastien Ourselin, M. Jorge Cardoso:
A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image Quality. 733-742 - Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan:
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study. 743-754 - Roger D. Soberanis-Mukul, Nassir Navab, Shadi Albarqouni:
Uncertainty-based Graph Convolutional Networks for Organ Segmentation Refinement. 755-769 - David Tellez, Diederik Höppener, Cornelis Verhoef, Dirk J. Grünhagen, Pieter Nierop, Michal Drozdzal, Jeroen van der Laak, Francesco Ciompi:
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. 770-783 - Chen-Han Tsai, Nahum Kiryati, Eli Konen, Iris Eshed, Arnaldo Mayer:
Knee Injury Detection using MRI with Efficiently-Layered Network (ELNet). 784-794 - Jing Wang, Yiwei Chen, Wanyue Li, Wen Kong, Yi He, Chuihui Jiang, Guohua Shi:
Domain adaptation model for retinopathy detection from cross-domain OCT images. 795-810 - David A. Wood, Jeremy Lynch, Sina Kafiabadi, Emily Guilhem, Aisha Al Busaidi, Antanas Montvila, Thomas Varsavsky, Juveria Siddiqui, Naveen Gadapa, Matthew Townend, Martin Kiik, Keena Patel, Gareth J. Barker, Sébastien Ourselin, James H. Cole, Thomas C. Booth:
Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM). 811-826 - Nan Wu, Stanislaw Jastrzebski, Jungkyu Park, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
Improving the Ability of Deep Neural Networks to Use Information from Multiple Views in Breast Cancer Screening. 827-842 - Chensu Xie, Hassan Muhammad, Chad M. Vanderbilt, Raul Caso, Dig Vijay Kumar Yarlagadda, Gabriele Campanella, Thomas J. Fuchs:
Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning. 843-856 - Ziyue Xu, Xiaosong Wang, Hoo-Chang Shin, Dong Yang, Holger Roth, Fausto Milletari, Ling Zhang, Daguang Xu:
Correlation via Synthesis: End-to-end Image Generation and Radiogenomic Learning Based on Generative Adversarial Network. 857-866 - Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Greg Zaharchuk, Daniel L. Rubin:
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives. 867-880 - Evan M. Yu, Juan Eugenio Iglesias, Adrian V. Dalca, Mert R. Sabuncu:
An Auto-Encoder Strategy for Adaptive Image Segmentation. 881-891 - Jinwei Zhang, Hang Zhang, Mert R. Sabuncu, Pascal Spincemaille, Thanh D. Nguyen, Yi Wang:
Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping. 892-902 - Yichi Zhang, Lin Yuan, Yujia Wang, Jicong Zhang:
SAU-Net: Efficient 3D Spine MRI Segmentation Using Inter-Slice Attention. 903-913 - Jing Zhang, Caroline Petitjean, Pierre Lopez, Samia Ainouz:
Direct estimation of fetal head circumference from ultrasound images based on regression CNN. 914-922 - Maya Zohar, Omri Bar, Daniel Neimark, Gregory D. Hager, Dotan Asselmann:
Accurate Detection of Out of Body Segments in Surgical Video using Semi-Supervised Learning. 923-936
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