Automatic segmentation of the wire frame of stent grafts from CT data

2012 ◽  
Vol 16 (1) ◽  
pp. 127-139 ◽  
Author(s):  
Almar Klein ◽  
J. Adam van der Vliet ◽  
Luuk J. Oostveen ◽  
Yvonne Hoogeveen ◽  
Leo J. Schultze Kool ◽  
...  
Keyword(s):  
Automatic Segmentation ◽  
Stent Grafts ◽  
Wire Frame ◽  
The Wire ◽  
Ct Data

Reduction of Flow Rate Into a Saccular Aneurysm After Stenting

2002 ◽  
Author(s):  
Liang-Der Jou
Keyword(s):  
Blood Supply ◽  
Flow Rate ◽  
Vascular Diseases ◽  
Saccular Aneurysm ◽  
Frame Structures ◽  
Stent Grafts ◽  
Small Vessels ◽  
Wire Frame ◽  
Aneurysm Thrombosis ◽  
Open Stent

Stents, wire-frame structures, are very effective devices in the treatment of vascular diseases, such as stenoses and aneurysms. One-third of patients who have stent placements develop restenosis over a six-month period, with the cause thought to be hemodynamic-related. The use of stent grafts to treat aneurysms often leads to exclusion of smaller vessels adjacent to the aneurysm from the circulation, and success of this procedure may therefore depend on the size of small vessels being occluded. An open stent is preferred to preserve the blood supply to neighboring vessels, but is considered to be less effective in aneurysm thrombosis and in reducing the pressure inside the aneurysm.

scholarly journals Automatic Segmentation of the Abdominal Aorta and Stent-Grafts

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Bertram Sabrowsky-Hirsch ◽  
◽  
Stefan Thumfart ◽  
Wolfgang Fenz ◽  
Richard Hofer ◽  
...  
Keyword(s):  
Abdominal Aorta ◽  
Automatic Segmentation ◽  
Stent Grafts

Generation of Surface Models of 3D Objects From Their Wire-Frame Models

1992 ◽  
Author(s):  
S. Gupta ◽  
A. Shirkhodaie ◽  
A. H. Soni
Keyword(s):  
Common Vertex ◽  
Surface Model ◽  
Edge Information ◽  
Frame Model ◽  
3D Objects ◽  
Wire Frame ◽  
Surface Models ◽  
Plane Passing ◽  
Generate Surface ◽  
The Wire

Abstract This paper presents an algorithm to generate surface models of 3D objects from their wire-frame models. The algorithm firstly, obtains information about edges of the object from the wire-frame model of the object and uses this edge information to generate the pairs. A pair of an object is a combination of two non-collinear edges which have a common vertex. The algorithm then determines the unique plane passing through each pair and groups the coplanar pairs together. Then it sorts each of the groups of coplanar pairs to form one or more loops of edges. Finally for each group of coplanar pairs, all the loops are combined, using a few rules, to form faces of the object. Hence a surface model of the object is generated.

An Automatic Segmentation and Reconstruction of Mandibular Structures from CT-Data

2009 ◽  
pp. 649-655 ◽  
Author(s):  
Iñigo Barandiaran ◽  
Iván Macía ◽  
Eva Berckmann ◽  
Diana Wald ◽  
Michael Pierre Dupillier ◽  
...  
Keyword(s):  
Automatic Segmentation ◽  
Ct Data

scholarly journals Improved diagnosis and navigation for CT colonography

2021 ◽  
Author(s):  
Jinjie Ming
Keyword(s):  
Ct Colonography ◽  
Automatic Segmentation ◽  
Segmentation Method ◽  
Polyp Detection ◽  
Data Set ◽  
Colon Wall ◽  
Texture Information ◽  
Ct Data ◽  
New Feature ◽  
Shape And Size

This project describes the development of an automatic segmentation method and a novel navigation system that detect polyps using advanced image processing and computer graphics tecniques. The colon wall segmentation method from the CT data set of abdomen is achieved by combining the contouring model - level set method and the minima detection using mathematical morphology theory. Polyp detection is attained by analyzing surface curvature and texture information along on the colon wall. Adding texture analysis provides a new feature for improving currently existing methods. As such, polyp candidates are examined not only by their shape and size but also by their texture appearance.

scholarly journals Cascaded Dilated Deep Residual Network for Volumetric Liver Segmentation From CT Image

2021 ◽  
Vol 12 (1) ◽  
pp. 34-45
Author(s):  
Gajendra Kumar Mourya ◽  
Manashjit Gogoi ◽  
S. N. Talbar ◽  
Prasad Vilas Dutande ◽  
Ujjwal Baid
Keyword(s):  
Evaluation System ◽  
Automatic Segmentation ◽  
Input Image ◽  
Liver Segmentation ◽  
Residual Network ◽  
Online Evaluation ◽  
Volumetric Ct ◽  
Ct Data ◽  
Symmetric Surface ◽  
Evaluation Parameters

Volumetric liver segmentation is a prerequisite for liver transplantation and radiation therapy planning. In this paper, dilated deep residual network (DDRN) has been proposed for automatic segmentation of liver from CT images. The combination of three parallel DDRN is cascaded with fourth DDRN in order to get final result. The volumetric CT data of 40 subjects belongs to “Combined Healthy Abdominal Organ Segmentation” (CHAOS) challenge 2019 is utilized to evaluate the proposed method. Input image converted into three images using windowing ranges and fed to three DDRN. The output of three DDRN along with original image fed to the fourth DDRN as an input. The output of cascaded network is compared with the three parallel DDRN individually. Obtained results were quantitatively evaluated with various evaluation parameters. The results were submitted to online evaluation system, and achieved average dice coefficient is 0.93±0.02; average symmetric surface distance (ASSD) is 4.89±0.91. In conclusion, obtained results are prominent and consistent.

scholarly journals Improved diagnosis and navigation for CT colonography

2021 ◽  
Author(s):  
Jinjie Ming
Keyword(s):  
Ct Colonography ◽  
Automatic Segmentation ◽  
Segmentation Method ◽  
Polyp Detection ◽  
Data Set ◽  
Colon Wall ◽  
Texture Information ◽  
Ct Data ◽  
New Feature ◽  
Shape And Size

This project describes the development of an automatic segmentation method and a novel navigation system that detect polyps using advanced image processing and computer graphics tecniques. The colon wall segmentation method from the CT data set of abdomen is achieved by combining the contouring model - level set method and the minima detection using mathematical morphology theory. Polyp detection is attained by analyzing surface curvature and texture information along on the colon wall. Adding texture analysis provides a new feature for improving currently existing methods. As such, polyp candidates are examined not only by their shape and size but also by their texture appearance.

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