東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

3D image reconstruction from serial ...

Liu, Yang.

FindBook

Google Book

Amazon

博客來

3D image reconstruction from serial sections.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	3D image reconstruction from serial sections./
作者:	Liu, Yang.
面頁冊數:	118 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
Contained By:	Dissertation Abstracts International75-09B(E).
標題:	Applied mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3622096
ISBN:	9781303936760

3D image reconstruction from serial sections.
Liu, Yang.

3D image reconstruction from serial sections. - 118 p.

Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.

Thesis (Ph.D.)--University of Pennsylvania, 2014.

This item must not be sold to any third party vendors.

Analyzing 3D anatomical structures plays an important role in modern biology and medical science. Despite the fast development of 3D medical imaging techniques such as MRI and CT, 2D imaging methods such as microscopy still excel in terms of spatial resolution and the anatomical details in fine tissue structures. This calls for an effective volumetric image reconstruction method to find theorrespondence among a sequence of 2D images and recover the 3D coherence that is lost in the sampling process. In this dissertation, we introduce a novel general framework for modeling volumetric image reconstruction with a rigorous and symmetric formulation. The formulation is robust to the noise and corrupted slices by using a greater range of adaptive weights in the regularization energy. The geometrical shape difference between sections is explicitly encoded via large deformation models which provide a mathematical method to quantitatively measure the shape change. Finally, a polyaffine image transformation model is presented which combines the power of deformation and the simplicity of the affine transformation.

ISBN: 9781303936760Subjects--Topical Terms:

2122814
Applied mathematics.

3D image reconstruction from serial sections.
LDR:02132nmm a2200301 4500 001 2059953
005 20150822105424.5
008 170521s2014 ||||||||||||||||| ||eng d
020 $a 9781303936760
035 $a (MiAaPQ)AAI3622096
035 $a AAI3622096
040 $a MiAaPQ $c MiAaPQ
100 1 $a Liu, Yang. $3 1026508
245 1 0 $a 3D image reconstruction from serial sections.
300 $a 118 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
500 $a Advisers: James C. Gee; Charles L. Epstein.
502 $a Thesis (Ph.D.)--University of Pennsylvania, 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Analyzing 3D anatomical structures plays an important role in modern biology and medical science. Despite the fast development of 3D medical imaging techniques such as MRI and CT, 2D imaging methods such as microscopy still excel in terms of spatial resolution and the anatomical details in fine tissue structures. This calls for an effective volumetric image reconstruction method to find theorrespondence among a sequence of 2D images and recover the 3D coherence that is lost in the sampling process. In this dissertation, we introduce a novel general framework for modeling volumetric image reconstruction with a rigorous and symmetric formulation. The formulation is robust to the noise and corrupted slices by using a greater range of adaptive weights in the regularization energy. The geometrical shape difference between sections is explicitly encoded via large deformation models which provide a mathematical method to quantitatively measure the shape change. Finally, a polyaffine image transformation model is presented which combines the power of deformation and the simplicity of the affine transformation.
590 $a School code: 0175.
650 4 $a Applied mathematics. $3 2122814
650 4 $a Medical imaging. $3 3172799
690 $a 0364
690 $a 0574
710 2 $a University of Pennsylvania. $b Applied Mathematics and Computational Science. $3 2094759
773 0 $t Dissertation Abstracts International $g 75-09B(E).
790 $a 0175
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3622096