Simulation and Synthesis in Medical Imaging: Third International Workshop, SASHIMI 2018, Held in Con
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- Artikel-Nr.: 10382356
Beschreibung
Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks.- Data Augmentation Using synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI.- Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation.- Cross-modality Image Synthesis from Unpaired Data Using CycleGAN: Effects of Gradient Consistency Loss and Training Data Size.- A Machine Learning Approach to Diffusion MRI Partial Volume Estimation.- Unsupervised Learning for Cross-domain Medical Image Synthesis Using Deformation Invariant Cycle Consistency Networks.- Deep Boosted Regression for MR TO CT Synthesis.- Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Multiple Mutually Interacting Motile Cells with Filopodia.- MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net for Multi-Modal Alzheimer's Classification.- Tubular Network Formation Process Using 3D Cellular Potts Model.- Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images.- Lung Nodule Synthesis Using CNN-based Latent Data Representation.- RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours.- Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models.
Eigenschaften
Breite: | 157 |
Gewicht: | 242 g |
Höhe: | 236 |
Länge: | 10 |
Seiten: | 140 |
Sprachen: | Englisch |
Autor: | Ali Gooya, Ipek Oguz, Ninon Burgos, Orcun Goksel |
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