Buch, Englisch, 581 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 896 g
Reihe: Topics in Biomedical Engineering. International Book Series
Theory and Biomaterial Applications
Buch, Englisch, 581 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 896 g
Reihe: Topics in Biomedical Engineering. International Book Series
ISBN: 978-1-4939-0213-2
Verlag: Springer
Deformable Models: Theory and Biomaterial Applications focuses on the core image processing techniques: theory and biomaterials useful to research and industry.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Bildgebende Verfahren, Nuklearmedizin, Strahlentherapie Radiologie, Bildgebende Verfahren
- Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
Weitere Infos & Material
T-Surfaces Framework For Offset Generation And Semiautomatic 3d Segmentation.- Parametric Contour Model In Medical Image Segmentation.- Deformable Models And Their Application In Segmentation Of Imaged Pathology Specimens.- Image Segmentation Using The Level Set Method.- Parallel Co-Volume Subjective Surface Method For 3d Medical Image Segmentation.- Volumetric Segmentation Using Shape Models In The Level Set Framework.- Medical Image Segmentation Based On Deformable Models And Its Applications.- Breast Strain Imaging: A Cad Framework.- Alternate Spaces For Model Deformation: Application Of Stop And Go Active Models To Medical Images.- Deformable Model-Based Segmentation Of The Prostate From Ultrasound Images.- Segmentation Of Brain Mr Images Using J-Divergence Based Active Contour Models.- Morphometric Analysis Of Normal And Pathologic Brain Structure Via High-Dimensional Shape Transformations.- Efficient Kernel Density Estimation Of Shape And Intensity Priors For Level Set Segmentation.- Volumetric Mri Analysis Of Dyslexic Subjects Using A Level Set Framework.- Analysis Of 4-D Cardiac Mr Data With Nurbs Deformable Models: Temporal Fitting Strategy And Nonrigid Registration.- Robust Neuroimaging-Based Classification Techniques Of Autistic Vs. Typically Developing Brain.