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Incomplete multi-modal representation learning for Alzheimer’s disease diagnosis, Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study, Evaluation of a novel navigation platform for laparoscopic liver surgery with organ deformation compensation using injected fiducials, Model-informed machine learning for multi-component T2 relaxometry, Compressive MRI quantification using convex spatiotemporal priors and deep encoder-decoder networks, CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation, High-resolution 3D abdominal segmentation with random patch network fusion, Automated interpretation of congenital heart disease from multi-view echocardiograms, Image registration: Maximum likelihood, minimum entropy and deep learning, A novel chromosome cluster types identification method using ResNeXt WSL model, Graph convolution network with similarity awareness and adaptive calibration for disease-induced deterioration prediction, Combining unsupervised and supervised learning for predicting the final stroke lesion, TSegNet: An efficient and accurate tooth segmentation network on 3D dental model, Cascaded convolutional networks for automatic cephalometric landmark detection, Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution, A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification, ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate, Non-invasive estimation of relative pressure for intracardiac flows using virtual work-energy, An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization, Estimating cardiomyofiber strain in vivo by solving a computational model, Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction, Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization, Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers, Test-time adaptable neural networks for robust medical image segmentation, Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration, Compressed sensing plus motion (CS + M): A new perspective for improving undersampled MR image reconstruction, DeepTarget: Gross tumor and clinical target volume segmentation in esophageal cancer radiotherapy, Gaussianization of Diffusion MRI Data Using Spatially Adaptive Filtering, Brain graph synthesis by dual adversarial domain alignment and target graph prediction from a source graph, Hypergraph learning for identification of COVID-19 with CT imaging, COVID-AL: The diagnosis of COVID-19 with deep active learning, Deeply-supervised density regression for automatic cell counting in microscopy images, Dynamic MRI reconstruction with end-to-end motion-guided network, A hybrid network for automatic hepatocellular carcinoma segmentation in H&E-stained whole slide images, Multi-Regression based supervised sample selection for predicting baby connectome evolution trajectory from neonatal timepoint, Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer, Identifying brain areas correlated with ADOS raw scores by studying altered dynamic functional connectivity patterns, Structured layer surface segmentation for retina OCT using fully convolutional regression networks, Improving statistical power of glaucoma clinical trials using an ensemble of cyclical generative adversarial networks, HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images, An integrated time adaptive geographic atrophy prediction model for SD-OCT images, Toward real-time polyp detection using fully CNNs for 2D Gaussian shapes prediction, A deep community based approach for large scale content based X-ray image retrieval, Capsules for biomedical image segmentation, Automated size-specific dose estimates using deep learning image processing, A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set, Accurate brain age prediction with lightweight deep neural networks, End-to-end multimodal image registration via reinforcement learning, Roto-translation equivariant convolutional networks: Application to histopathology image analysis, Download the ‘Understanding the Publishing Process’ PDF, Check the status of your submitted manuscript in the. 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