NDLI: Mitral annulus segmentation from four-dimensional ultrasound using a valve state predictor and constrained optical flow

Please wait, while we are loading the content...

Mitral annulus segmentation from four-dimensional ultrasound using a valve state predictor and constrained optical flow

Content Provider	PubMed Central
Author	Schneider, Robert J. Perrin, Douglas P. Vasilyev, Nikolay V. Marx, Gerald R. Nido, Pedro J. Del Howe, Robert D.
Copyright Year	2011
Abstract	Measurement of the shape and motion of the mitral valve annulus has proven useful in a number of applications, including pathology diagnosis and mitral valve modeling. Current methods to delineate the annulus from four-dimensional (4D) ultrasound, however, either require extensive overhead or user-interaction, become inaccurate as they accumulate tracking error, or they do not account for annular shape or motion. This paper presents a new 4D annulus segmentation method to account for these deficiencies. The method builds on a previously published three-dimensional (3D) annulus segmentation algorithm that accurately and robustly segments the mitral annulus in a frame with a closed valve. In the 4D method, a valve state predictor determines when the valve is closed. Subsequently, the 3D annulus segmentation algorithm finds the annulus in those frames. For frames with an open valve, a constrained optical flow algorithm is used to the track the annulus. The only inputs to the algorithm are the selection of one frame with a closed valve and one user-specified point near the valve, neither of which needs to be precise. The accuracy of the tracking method is shown by comparing the tracking results to manual segmentations made by a group of experts, where an average RMS difference of 1.67 ± 0.63 mm was found across 30 tracked frames.
Related Links	http://dx.doi.org/10.1016/j.media.2011.11.006
Ending Page	504
Page Count	8
Starting Page	497
File Format	PDF
ISSN	13618415
e-ISSN	13618423
Journal	Medical Image Analysis
Issue Number	2
Volume Number	16
Language	English
Publisher Date	2012-02-01
Access Restriction	Open
Subject Keyword	Radiological and Ultrasound Technology Health Informatics Radiology Nuclear Medicine and imaging Computer Vision and Pattern Recognition Computer Graphics and Computer-Aided Design Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Radiology, Nuclear Medicine and Imaging Health Informatics Computer Vision and Pattern Recognition Radiological and Ultrasound Technology

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

A statistically based flow for image segmentation

Segmentation of 3D Radio Frequency Echocardiography Using a Spatio-temporal Predictor

THREE-DIMENSIONAL COUPLED-OBJECT SEGMENTATION USING SYMMETRY AND TISSUE TYPE INFORMATION

Consistent Segmentation using a Rician Classifier

Segmentation with Area Constraints

Semi-automatic Segmentation for Prostate Interventions

Gaussian Mixtures on Tensor Fields for Segmentation: Applications to Medical Imaging

GPU Based Real-time Instrument Tracking with Three Dimensional Ultrasound

Homeomorphic Brain Image Segmentation with Topological and Statistical Atlases

Mitral annulus segmentation from four-dimensional ultrasound using a valve state predictor and constrained optical flow

Similar Documents

A statistically based flow for image segmentation

Segmentation of 3D Radio Frequency Echocardiography Using a Spatio-temporal Predictor

THREE-DIMENSIONAL COUPLED-OBJECT SEGMENTATION USING SYMMETRY AND TISSUE TYPE INFORMATION

Consistent Segmentation using a Rician Classifier

Segmentation with Area Constraints

Semi-automatic Segmentation for Prostate Interventions

Gaussian Mixtures on Tensor Fields for Segmentation: Applications to Medical Imaging

GPU Based Real-time Instrument Tracking with Three Dimensional Ultrasound

Homeomorphic Brain Image Segmentation with Topological and Statistical Atlases

Mitral annulus segmentation from four-dimensional ultrasound using a valve state predictor and constrained optical flow