Surgery – Diagnostic testing – Detecting nuclear – electromagnetic – or ultrasonic radiation
Reexamination Certificate
1999-02-19
2001-06-26
Lateef, Marvin M. (Department: 3737)
Surgery
Diagnostic testing
Detecting nuclear, electromagnetic, or ultrasonic radiation
C128S916000
Reexamination Certificate
active
06251072
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to a semi-automated method for constructing and displaying 3-D ultrasound images. In particular, the semi-automated method provides 3-D ultrasound images of luminal surfaces of blood vessels.
BACKGROUND OF THE INVENTION
The severity of atherosclerosis at the carotid artery bifurcation is correlated with the occurrence of stroke.
1,2
Since most strokes associated with carotid atherosclerosis can be prevented by surgical or non-surgical treatment
3
, the identification and monitoring of carotid disease is important for the management of patients at risk of stroke. Currently, conventional means of diagnosing and assessing the progression of atherosclerosis involve either determining the degree of stenosis with x-ray angiography or MRA, or with techniques which are sensitive to abnormalities in blood flow rate, such as Doppler ultrasonography. Unfortunately, none of these known techniques provide a clear three-dimensional (3-D) image of the target tissue in a manner which allows for the non-invasive and detailed view of the blood vessels. Moreover, none of the known techniques provide detailed visualization of the lumen surfaces of blood vessels within the body.
It is therefore an object of the present invention to provide a novel method, based on 3-D ultrasound, which is non-invasive and provides detailed three-dimensional views of internal luminal surfaces of blood vessels. An important task in the development of such a technique is the segmentation (i.e., extraction) of vessel surfaces from ultrasound images for the purposes of visualization, therapy planning, and volumetric measurements. Deformable surface models have become particularly useful tools for this method.
4
SUMMARY OF THE INVENTION
According to one aspect of the present invention there is provided a semi-automatic 3-D ultrasound segmentation method for displaying luminal surfaces of vessels, the method comprising the steps of:
(a) acquiring a 3-D ultrasound image of a target vessel; and
(b) segmenting the luminal surfaces from the 3-D ultrasound image of the target vessel to generate a 3-D ultrasound image of the lumen of the target vessel; wherein an inflating balloon model is used for segmenting the luminal surfaces of the target vessel.
In another aspect of the present invention, there is provided a method for the diagnosis and prognosis of vessel disease, the method comprising the steps of:
(a) acquiring a 3-D ultrasound image of a target vessel;
(b) segmenting the luminal surfaces from the 3-D ultrasound image of the target vessel to generate a 3-D ultrasound image of the lumen of the target vessel using an inflating balloon model;
(c) inspecting the generated 3-D ultrasound image of the lumen of the target vessel to assess the presence of a shadow representing a disease lesion within the lumen.
REFERENCES:
patent: 5601084 (1997-02-01), Sheehan et al.
Sherebrin, Shi, et al., Freehand Three-Dimensional Ultrasound: Implementation and Applications,SPIE, vol. 2708, pp. 296-303 (Feb. 1996).
Terzopoulos, Demetri, et al., Sampling and Reconstruction with Adaptive Meshes,Proceedings of the Conference on Computer Vision and Pattern Recognition, pp. 70-75 (Jun. 1991).
Fenster, Aaron, et al., 3-D Ultrasound Imaging: A Review,IEEE Engineering in Medicine and Biology, pp. 41-51 (Nov./Dec. 1996).
Barnett, et al., Beneficial Effect Of Carotid Endarterectomy In Symptomatic Patients With High-Grade Carotid Stenosis,The New England Journal of Medicine, vol 325, No. 7, pp. 445-453 (Aug. 1991).
I. Dehaene, et al., MRC European Carotid Surgery Trial: Interim Results For Symptomatic Patients With Severe (70-99%) Or With Mild (0-29%) Carotid Stenosis,The Lancet, vol. 337, No. 8752, pp. 1235-1243 (May 1991).
Gorelick, Philip B., MD, MPH, FACP, Stroke Prevention. An Opportunity For Efficient Utilization Of Health Care Resources During The Coming Decade,Stroke, vol. 25, No. 1, pp. 220-224 (Jan. 1994).
McInerney, Tim, et al., Deformable Models In Medical Image Analysis: A Survey,Medical Image Analysis, vol. 1, No. 2, pp. 91-108 (1996).
Chen, Yang, et al., Description Of Complex Objects From Multiple Range Images Using An Inflating Balloon Model,Computer Vision and Image Understanding, vol. 61, No. 3, pp. 325-334 (May 1995).
Young, Ian T., et al., Recursive Implementation Of The Gaussian Filter,Signal Processing, vol. 44, pp. 140-151 (1995).
Bouma, Carolien J., et al., Evaluation Of Segmentation Algorithms For Intravascular Ultrasound Images,Lecture Notes in Computer Science, vol. 1131, pp. 203-212 (1996).
Carrascal, Francisco M., et al., Automatic Calculation Of Total Lung Capacity From Automatically Traced Lung Boundaries In Postero-Anterior And Lateral Digital Chest Radiographs,Medical Physics, vol. 25, No. 7, pp. 1118-1131 (Jul. 1998).
Duryea, Jeff, et al., A Fully Automated Algorithm For The Segmentation Of Lung Fields On Digital Chest Radiographic Images,Medical Physics, vol. 22, No. 2, pp. 183-191 (Feb. 1995).
Miller, James V., et al., Geometrically Deformed Models: A Method For Extracting Closed Geometric Models From Volume Data,Computer Graphics, vol. 25, No. 4, pp. 217-226 (Jul. 1991).
Arbeille, Ph., MD, PhD, et al., Quantification and Assessment Of Carotid Artery Lesions: Degree Of Stenosis And Plaque Volume,Journal of Clinical Ultrasound, vol. 23, No. 2, pp. 113-124 (Feb. 1995).
Hatsukami, Thomas S., et al., Echolucent Regions In Carotid Plaque: Preliminary Analysis Comparing Three-Dimensional Histologic Reconstructions To Sonographic Findings,Ultrasound in Medicine and Biology, vol. 20, No. 8, pp. 743-749 (1994).
Lobregt, Steven, et al., A Discrete Dynamic Contour Model,IEEE, pp. 12-24 (1995).
Kass, Michael, et al., Snakes: Active Contour Models,International Journal of computer Vision, pp. 321-331 (1988).
Steinke, et al., Three-dimensional Ultrasound Imaging of Carotid Artery Plaque,Journal of Cardiovascular Technology, vol. 8, No. 1, pp. 15-22 (1989).
Gonzales et al., Digital Image Processing,Addison-Wesley Publishing Company, Second Edition, pp. 369-373 (1987).
Fenster Aaron
Gill Jeremy D.
Ladak Hanif M.
Steinman David A.
Fulwider Patton Lee & Utecht LLP
Imam Ali M.
Lateef Marvin M.
Life Imaging Systems Inc.
LandOfFree
Semi-automated segmentation method for 3-dimensional ultrasound does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Semi-automated segmentation method for 3-dimensional ultrasound, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Semi-automated segmentation method for 3-dimensional ultrasound will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2527743