مش های دگردیس پذیر برای تقسیم بندی تصویر پزشکی – تقسیم بندی خودکار دقیق از ساختار های آناتومیکی Deformable Meshes for Medical Image Segmentation
- نوع فایل : کتاب
- زبان : انگلیسی
- نویسنده : Dagmar Kainmueller
- چاپ و سال / کشور: 2015
- تعداد صفحه : 184
Description
Deformable Meshes for Medical Image Segmentation - Accurate Automatic Segmentation of Anatomical Structures - Aktuelle Forschung Medizintechnik - Latest Research in Medical Engineering
Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author’s core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatomical structures, together with thorough evaluations of segmentation accuracy on clinical image data. As compared to related work, these fully automatic pipelines allow for highly accurate segmentation of benchmark image data
Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author’s core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatomical structures, together with thorough evaluations of segmentation accuracy on clinical image data. As compared to related work, these fully automatic pipelines allow for highly accurate segmentation of benchmark image data
