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Bibliografische gegevens
Hoofdauteurs:	Panfilov, Egor, Tiulpin, Aleksei, Klein, Stefan, Nieminen, Miika T., Saarakkala, Simo
Formaat:	Preprint
Gepubliceerd in:	2019
Onderwerpen:	Image and Video Processing Computer Vision and Pattern Recognition
Online toegang:	https://arxiv.org/abs/1908.04126
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!

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The Role of Radiographic Knee Alignment in Total Knee Replacement Outcomes and Opportunities for Artificial Intelligence-Driven Assessment
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Toward Cost-efficient Adaptive Clinical Trials in Knee Osteoarthritis with Reinforcement Learning
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Deep Domain Isolation and Sample Clustered Federated Learning for Semantic Segmentation
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Minimally Interactive Segmentation of Soft-Tissue Tumors on CT and MRI using Deep Learning
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Deep Learning-Based Approach for Automatic 2D and 3D MRI Segmentation of Gliomas
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Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation
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Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputs
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Segmentation of Brain Metastases in MRI: A Two-Stage Deep Learning Approach with Modality Impact Study
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Deep Learning for Accelerated and Robust MRI Reconstruction: a Review
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Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI
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Robust Physics-based Deep MRI Reconstruction Via Diffusion Purification
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Deep Covariance Alignment for Domain Adaptive Remote Sensing Image Segmentation
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Deep Learning-Based Prediction of PET Amyloid Status Using Multi-Contrast MRI
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Diffusion and Multi-Domain Adaptation Methods for Eosinophil Segmentation
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Simultaneous Deep Learning of Myocardium Segmentation and T2 Quantification for Acute Myocardial Infarction MRI
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TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI
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Unsupervised Domain Adaptation for Pediatric Brain Tumor Segmentation
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Deep Learning for Automated Wound Classification And Segmentation
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Validation of Fully-Automated Deep Learning-Based Fibroglandular Tissue Segmentation for Efficient and Reliable Quantitation of Background Parenchymal Enhancement in Breast MRI
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Deep Learning-Based Automated Post-Operative Gross Tumor Volume Segmentation in Glioblastoma Patients
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