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Three dimensional deformable image r...

Zhang, Miao.

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Three dimensional deformable image registration and registration verification.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Three dimensional deformable image registration and registration verification./
作者:	Zhang, Miao.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2015,
面頁冊數:	65 p.
附註:	Source: Masters Abstracts International, Volume: 56-01.
Contained By:	Masters Abstracts International56-01(E).
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10178644
ISBN:	9781369287721

Three dimensional deformable image registration and registration verification.
Zhang, Miao.

Three dimensional deformable image registration and registration verification. - Ann Arbor : ProQuest Dissertations & Theses, 2015 - 65 p.

Source: Masters Abstracts International, Volume: 56-01.

Thesis (M.S.)--University of Missouri - Columbia, 2015.

Deformable image registration (DIR) is a fundamental problem in medical image processing. Due to the lack of ground truth, such problem known as registration verification without 'golden standard' standard is still an unsolved scientific question. We propose to apply well developed techniques in the computer vision field, including the feature/region/edge based detectors, descriptors and matching for deformable image registration and registration verification.

ISBN: 9781369287721Subjects--Topical Terms:

523869
Computer science.

Three dimensional deformable image registration and registration verification.
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500 $a Source: Masters Abstracts International, Volume: 56-01.
500 $a Adviser: Ye Duan.
502 $a Thesis (M.S.)--University of Missouri - Columbia, 2015.
520 $a Deformable image registration (DIR) is a fundamental problem in medical image processing. Due to the lack of ground truth, such problem known as registration verification without 'golden standard' standard is still an unsolved scientific question. We propose to apply well developed techniques in the computer vision field, including the feature/region/edge based detectors, descriptors and matching for deformable image registration and registration verification.
520 $a Specifically, this thesis explores the feasibility of applying three dimensional scale invariant feature transform (SIFT), Harris-Laplace and maximally stable extremal regions (MSER), canny edge and iterative closest point (ICP) in the verification of registering magnetic resonance imaging (MRI) and computed tomography (CT) volume data. Our preliminary results show that the feature points/edges/regions provided by the aforementioned techniques are good candidates for the 'golden standard' key points. These features may be used as a powerful aid to human experts or even may be used alone in registration verification.
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