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Method for Segmentation of Structures in the Serially Sectioned Images of the Entire Body and Surface Reconstruction to Make Three-Dimensional Images

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dc.contributor.author황, 성배-
dc.date.accessioned2011-03-09T05:18:40Z-
dc.date.available2011-03-09T05:18:40Z-
dc.date.issued2007-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/1614-
dc.description.abstract"Propose : First purpose of this research is to prepare the segmented images of whole body in detail, which are distributed to help other investigators make 3D images and virtual dissection software of whole body. Second purpose is to present of semi-automatic surface reconstruction on the commercial software, which enables any researchers to do surface reconstruction quickly and objectively for making 3D images without the help of computer engineers.

Materials & Methods : Three-hundred nineteen structures (114 left lower limb structures, 105 head and neck structures, 15 heart structures, 85 left upper limb structures) of whole body were decided to segment in 1,702 temporary segmented images (PSD file, interval 1.0 mm, resolution 2,468 X 1,407) including anatomical images. On the PhotoshopTM, selections which fit the structures' contours were drawn automatically, semi-automatically, or manually; subsequently, the selections were put into the layers. After filling the selections with colors, the temporary segmented images were converted to segmented images (TIFF files). The segmented images were staked to make coronal and sagittal segmented images for verifying segmentation. One-hundred fourteen structures (1 skin, 32 bones, 7 knee joint structures, 60 muscles, 7 arteries, 7 nerves) in left lower limb were decided to semi-automatic surface reconstruction on the commercial software. Steps of semi-automatic surface reconstruction were as follows. First, disassembled segmented images were made by disassembling selections. Second, contour images were made by stacking selections. Third, contour 3D images were made by filling contour gaps with surfaces. Fourth, 3D images were made by deleting contours. Fifth, assembled 3D images were made by assembling 3D images.

Results : Contours of the anatomical structures in the three-hundred nineteen structures segmented images were corrected, and verified by examining the coronal images, sagittal images, and browsing software of Visible Korean Human. On the Maya, the 3D images of selected anatomic structures in left lower limb could be displayed opaquely or semi-transparently and rotated, which revealed that the 3D images were fit for anatomic knowledge.

Conclusion : The segmentation techniques of this research can be used to segment many structures in other images quickly and correctly. These technical modifications of existing software will provide new solutions in medical education and research. Also, in this research, method of semi-automatic surface reconstruction on commercial software was developed. The method could enable other researchers to do surface reconstruction quickly and objectively for making 3D images."
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dc.description.tableofcontents"Ⅰ. 서론 1

Ⅱ. 연구대상 및 방법 4

A. 시신의 온몸을 연속절단해서 해부영상을 만듦. 4

B. 해부영상에서 보이는 구조물 319개를 구역화해서 구역화영상을 만듦. 6

1. 구역화할 구조물을 결정함. 6

2. 해부영상을 종이에 인쇄해서 구역화함. 11

3. 자동, 반자동, 수동으로 구역화함. 12

4. 이마구역화영상과 마루구역화영상을 만들어서 구역화영상을 확인함. 23

C. 왼다리의 임시구역화영상을 가지고 표면재구성해서 3차원영상을 만듦. 27

1. ""선택""을 분해해서 분해구역화영상을 만듦. 27

2. ""선택""을 쌓아서 등고선영상을 만듦. 29

3. 등고선 사이에 면을 채워서 등고선3차원영상을 만듦. 30

4. 등고선을 없애서 3차원영상을 만듦. 34

5. 3차원영상을 조립해서 조립3차원영상을 만듦. 35

Ⅲ. 결과 37

A. 구역화영상 37

B. 3차원영상 44

Ⅳ. 고찰 47

Ⅴ. 결론 66

참고 문헌 67

ABSTRACT 71"
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dc.language.isoko-
dc.titleMethod for Segmentation of Structures in the Serially Sectioned Images of the Entire Body and Surface Reconstruction to Make Three-Dimensional Images-
dc.title.alternative온몸의 연속절단면영상에서 구조물을 구역화하고 표면재구성해서 3차원영상을 만드는 방법-
dc.typeThesis-
dc.identifier.urlhttp://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000001759-
dc.subject.keyword연속절단면영상-
dc.subject.keyword3차원영상-
dc.subject.keyword구역화영상-
dc.subject.keyword표면재구성-
dc.subject.keyword왼다리의 해부-
dc.description.degreeDoctor-
dc.contributor.department대학원 의학과-
dc.contributor.affiliatedAuthor황, 성배-
dc.date.awarded2007-
dc.type.localTheses-
dc.citation.date2007-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
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Theses > School of Medicine / Graduate School of Medicine > Doctor
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