Buch, Englisch, 154 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 416 g
Progress in Research and Applications
Buch, Englisch, 154 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 416 g
Reihe: Lecture Notes in Bioengineering
ISBN: 978-3-031-94127-6
Verlag: Springer
This book presents contributions from the MICCAI 2024 Computational Biomechanics for Medicine Workshop CBM XIX. The peer-reviewed chapters of the book were presented during the 27 International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI held in Marrakesh, Morocco. The content focuses on applications of computational biomechanics to computer-integrated medicine, which includes medical image computing, application of machine learning in image analysis and biomechanics, new approaches to stress computing for biomechanics of soft tissues and evaluation of strain, new assumptions to computing pipelines for disease and injury mechanisms, novel algorithms of computational biomechanics, a unique application of artificial intelligence and neural network in computing and experimental methods for the analysis of disease and injury mechanisms. This book details the state-of-the-art and progress in above mentioned scientific fields for researchers, students, and professionals.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Physik Angewandte Physik Biophysik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Naturwissenschaften Physik Mechanik
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
Weitere Infos & Material
Validation of 4D ultrasound strain imaging of the aortic wall.- Reliable computational fluid dynamics for ground truth generation for AI-based blood flow analysis.- The comparison of 2D and 3D based models for the problem of plaque segmentation and coronary artery calcium scoring on non-contrast cardiac CT imaging.- Conditional Graph Neural Network for Predicting Soft Tissue Deformation and Forces.- Abdominal aortic aneurysm wall stress: A 7-line code in MATLAB and a one-click software application.
