Buch, Englisch, Band 11397, 181 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 300 g
Computational Methods and Clinical Applications for Spine Imaging
1. Auflage 2019
ISBN: 978-3-030-13735-9
Verlag: Springer International Publishing
5th International Workshop and Challenge, CSI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers
Buch, Englisch, Band 11397, 181 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 300 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-030-13735-9
Verlag: Springer International Publishing
This book constitutes the refereed proceedings of the 5th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018.
The 8 full papers presented together with 8 short papers and 1 keynote were carefully reviewed and selected for inclusion in this volume. Papers on novel methodology and clinical research, and also papers which demonstrate the performance of methods on the provided challenges, the aim is to cover both theoretical and very practical aspects of computerized spinal imaging.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
Weitere Infos & Material
Spinal Cord Gray Matter-White Matter Segmentation on Magnetic Resonance AMIRA Images with MD-GRU.- Predicting Scoliosis in DXA Scans Using Intermediate Representations.- Fast Registration of CT with Intra-operative Ultrasound Images for Spine Surgery.- Automated Grading of Modic Changes Using CNNs – Improving the Performance with Mix-up.- Error Estimation for Appearance Model Segmentation of Musculoskeletal Structures Using Multiple, Independent Sub-models.- Automated Segmentation of Intervertebral Disc using Fully Dilated Separable Deep Neural Networks.- Intensity Standardization of Skeleton in Follow-up Whole-Body MRI.- Towards a Deformable Multi-Surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning.- Intervertebral Disc Segmentation Using Mathematical Morphology—A CNN-Free Approach.
