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Titlebook: Deformable Meshes for Medical Image Segmentation; Accurate Automatic S Dagmar Kainmueller Book 2015 Springer Fachmedien Wiesbaden 2015 Auto

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發(fā)表于 2025-3-21 19:53:02 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Deformable Meshes for Medical Image Segmentation
副標題Accurate Automatic S
編輯Dagmar Kainmueller
視頻videohttp://file.papertrans.cn/265/264820/264820.mp4
概述Publication in the field of technical sciences?.Includes supplementary material:
叢書名稱Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering
圖書封面Titlebook: Deformable Meshes for Medical Image Segmentation; Accurate Automatic S Dagmar Kainmueller Book 2015 Springer Fachmedien Wiesbaden 2015 Auto
描述? 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.?
出版日期Book 2015
關鍵詞Automatic segmentation; Deformable surfaces; Medical Image Data; Segmentation of Medical Image Data; Seg
版次1
doihttps://doi.org/10.1007/978-3-658-07015-1
isbn_softcover978-3-658-07014-4
isbn_ebook978-3-658-07015-1Series ISSN 2625-9354 Series E-ISSN 2625-9362
issn_series 2625-9354
copyrightSpringer Fachmedien Wiesbaden 2015
The information of publication is updating

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發(fā)表于 2025-3-21 21:47:38 | 只看該作者
2625-9354 ta 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 D
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Book 2015urate 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-sh
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發(fā)表于 2025-3-22 13:27:06 | 只看該作者
From Surface Mesh Deformations to Volume Deformationsexhibit large non-linear . variations of shape that are of . nature rather than stemming from a statistical distribution. E.g., articulated bone compounds are subject to intra-individual shape variation stemming from articulation in joints. Such variations call for mechanical rather than statistical modeling (Kainmueller et al., 2009b).
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發(fā)表于 2025-3-22 19:32:59 | 只看該作者
Fundamentals of Quantitative Evaluations more accurate than method B. As for the quantification of segmentation accuracy, Section 6.1 introduces a set of measures that quantify the dissimilarity of one segmentation to another. These measures quantify differences between segmentations.
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https://doi.org/10.1007/978-3-642-68912-3the methodological and practical context in which this thesis was realized, lists the specific contributions of this work, and distinguishes related topics that are not discussed. Section 1.3 gives an overview of the structure of this thesis.
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