NDLI: Automatic extraction of aortic aneurysm from thoracic CTA based on Fuzzy-based 3-D region growing method

Content Provider	IEEE Xplore Digital Library
Author	Tokuyasu, T. Shuto, T. Yufu, K. Kanao, S. Marui, A. Komeda, M.
Copyright Year	2010
Description	Author affiliation: Graduate School of Medicine Kyoto University, Kyoto, Japan (Kanao, S.; Marui, A.) \|\| Department of Mechanical Engineering, Oita National College of Technology, Oita, Japan (Tokuyasu, T.; Shuto, T.; Yufu, K.) \|\| Nagoya Heart Center, Aichi, Japan (Komeda, M.)
Abstract	Computer-Aided Diagnosis (CAD) system that helps medical staffs to diagnose patient's disease conditions has been used in a variety fields of medicine. For cardiovascular surgery, radiologists manually construct 3-D volume model of patient organ and provide this information to cardiovascular surgeons, therefore automation technique for image processing of building patient 3-D volume model is highly requested from clinical site. The 3-D volume model is used in not only diagnosing patient disease condition, but also making a surgical plan before an operation. In the case of using CAD system for a cardiovascular disease patient, computed tomography angiography (CTA) has been used as the source data that clearly indicates the region of blood flow on the image due to contrast agent. However, sufficient information for the diagnosis is not obtained from CTA, because the regions of aneurysm and aortic wall tissue can not distinguished correctly even using the latest CAD system. Then, this study proposes Fuzzy-based region growing method that enables a computer to have the ability of reading radiogram. We focused on the skill of reading radiogram of experienced doctors, because they know the boundary line between aneurysm and aortic wall tissue on CTA image. Hence, Fuzzy inference has been employed to express doctor's skill of reading radiogram and used as the growing criteria. The proposed method is applied to one patient CTA data and its result is shown and discussed in this paper.
Starting Page	2090
Ending Page	2093
File Size	1042809
Page Count	4
File Format	PDF
ISBN	9781424474530
e-ISBN	9788993215021
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-27
Publisher Place	Korea (South)
Access Restriction	Subscribed
Rights Holder	IEEE International Conference on Control & Automation
Subject Keyword	Medical image processing Design automation Computer tomography angiography Surgery Aneurysm Fuzzy inference Software Pixel Medical diagnostic imaging
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Region growing on frangi vesselness values in 3-D CTA data

Automatic Segmentation of Abdominal Aortic Aneurysm in Computed Tomography Images Using Spatial Fuzzy C-Means

Detection of lung cancer nodules using automatic region growing method

Computed tomography angiography of thoracic aortic aneurysms.

Comprehensive comparison of three different workstations for accurate planning of endovascular stent implantation in patients with thoracic aortic aneurysms.

Pixel profiling for extraction of arteriovenous malformation in 3-D CTA images

Study on the clinical value of computed tomography angiography in the diagnosis of aortic aneurysm

3D automatic segmentation of coronary artery based on hierarchical region growing algorithm (3D HRG) in CTA data- sets

Postoperative imaging of the aorta.

Automatic extraction of aortic aneurysm from thoracic CTA based on Fuzzy-based 3-D region growing method

Similar Documents

Region growing on frangi vesselness values in 3-D CTA data

Automatic Segmentation of Abdominal Aortic Aneurysm in Computed Tomography Images Using Spatial Fuzzy C-Means

Detection of lung cancer nodules using automatic region growing method

Computed tomography angiography of thoracic aortic aneurysms.

Comprehensive comparison of three different workstations for accurate planning of endovascular stent implantation in patients with thoracic aortic aneurysms.

Pixel profiling for extraction of arteriovenous malformation in 3-D CTA images

Study on the clinical value of computed tomography angiography in the diagnosis of aortic aneurysm

3D automatic segmentation of coronary artery based on hierarchical region growing algorithm (3D HRG) in CTA data- sets

Postoperative imaging of the aorta.

Automatic extraction of aortic aneurysm from thoracic CTA based on Fuzzy-based 3-D region growing method