Papers
Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images
Jiechao Ma, Xiang Li, Hongwei Li et al.
Dynamic Pacemaker Artifact Removal (DyPAR) from CT Data using CNNs
Tanja Lossau (née Elss), Hannes Nickisch, Tobias Wissel et al.
Dense Segmentation in Selected Dimensions: Application to Retinal Optical Coherence Tomography
Bart Liefers, Cristina González-Gonzalo, Caroline Klaver et al.
DavinciGAN: Unpaired Surgical Instrument Translation for Data Augmentation
Kyungmoon Lee, Min-Kook Choi, Heechul Jung
Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning
Maxime W. Lafarge, Juan C. Caicedo, Anne E. Carpenter et al.
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data
Seyed Mostafa Kia, Andre F. Marquand
Boundary loss for highly unbalanced segmentation
Hoel Kervadec, Jihene Bouchtiba, Christian Desrosiers et al.
Dynamic MRI Reconstruction with Motion-Guided Network
Qiaoying Huang, Dong Yang, Hui Qu et al.
Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets: Application to IsoIntense Infant Brain MRI Segmentation
Seyed Raein Hashemi, Sanjay P. Prabhu, Simon K. Warfield et al.
Sparse Structured Prediction for Semantic Edge Detection in Medical Images
Lasse Hansen, Mattias P. Heinrich
Cluster Analysis in Latent Space: Identifying Personalized Aortic Valve Prosthesis Shapes using Deep Representations
Jannis Hagenah, Kenneth Kühl, Michael Scharfschwerdt et al.
Generative Image Translation for Data Augmentation of Bone Lesion Pathology
Anant Gupta, Srivas Venkatesh, Sumit Chopra et al.
Iterative learning to make the most of unlabeled and quickly obtained labeled data in histology
Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor et al.
Assessing Knee OA Severity with CNN attention-based end-to-end architectures
Marc Górriz, Joseph Antony, Kevin McGuinness et al.
Transfer Learning by Adaptive Merging of Multiple Models
Robin Geyer, Luca Corinzia, Viktor Wegmayr
Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations
Michael Gadermayr, Laxmi Gupta, Barbara M. Klinkhammer et al.
Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets
Reuben Dorent, Wenqi Li, Jinendra Ekanayake et al.
Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology
Thomas de Bel, Meyke Hermsen, Jesper Kers et al.
Deep Reinforcement Learning for Subpixel Neural Tracking
Tianhong Dai, Magda Dubois, Kai Arulkumaran et al.
Digitally Stained Confocal Microscopy through Deep Learning
Marc Combalia, Javiera Pérez-Anker, Adriana García-Herrera et al.
Deep Hierarchical Multi-label Classification of Chest X-ray Images
Haomin Chen, Shun Miao, Daguang Xu et al.
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
Nikolay Burlutskiy, Nicolas Pinchaud, Feng Gu et al.
Learning from sparsely annotated data for semantic segmentation in histopathology images
John-Melle Bokhorst, Hans Pinckaers, Peter van Zwam et al.
Learning interpretable multi-modal features for alignment with supervised iterative descent
Max Blendowski, Mattias P. Heinrich
Fusing Unsupervised and Supervised Deep Learning for White Matter Lesion Segmentation
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni et al.