Rules-based approach for processing medical images

Image analysis – Applications – Biomedical applications

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C382S274000, C378S028000

Reexamination Certificate

active

10260735

ABSTRACT:
A technique flexibly applies pre-programmed rules that specify the manner in which medical image data is to be classified or otherwise processed. A rules-based system selects from the pre-programmed rules, with different rules being used based on different doctors' preferences, such as during contrast agent studies. The rules-based system is initially “taught” how to apply a doctor's rules via a sample data image set, and then automatically applies the same rules to that doctor's image data whenever that image data is subsequently provided, thereby avoiding the need for doctors to constantly reconfigure a system with their own rules repetitively for each and every image or to otherwise place the burden of processing on the doctor. The programmed rules can include rules from the available literature—the doctors or other users are free to select from these available rules, modify/customize them to generate new rules, or provide completely new rules.

REFERENCES:
patent: 4839805 (1989-06-01), Pearson, Jr. et al.
patent: 5262945 (1993-11-01), DeCarli et al.
patent: 5311131 (1994-05-01), Smith
patent: 5627907 (1997-05-01), Gur et al.
patent: 5638465 (1997-06-01), Sano et al.
patent: 5644232 (1997-07-01), Smith
patent: 5768333 (1998-06-01), Abdel-Mottaleb
patent: 5818231 (1998-10-01), Smith
patent: 5920319 (1999-07-01), Vining et al.
patent: 6240201 (2001-05-01), Xu et al.
patent: 6310477 (2001-10-01), Schneider
patent: 6317617 (2001-11-01), Gilhuijs et al.
patent: 6687329 (2004-02-01), Hsieh et al.
patent: 6771822 (2004-08-01), Brackett
patent: 6956373 (2005-10-01), Brown et al.
patent: 8 69533 (1996-03-01), None
patent: WO 01/57777 (2001-08-01), None
Dasarathy, “Is Your Nearest Neighbor Near Enough a Neighbor?” inProceedings of the First International Conference on Information Sciences and Systems, Patras, Greece, 1976, pp. 114-117.
Bezdek, et al., “FCM: The Fuzzy c-Means Clustering Algorithm,”Computer&Geosciences, 10(2-3):191-203, 1984.
Vannier et al., “Multispectral Analysis of Magnetic Resonance Images,”Radiology, 154(1):221-224, 1985.
Xie et al., “A Validity Measure for Fuzzy Clustering,”IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(8):841-847, 1991.
Clarke et al., “Comparison of Supervised Pattern Recognition Techniques and Unsupervised Methods for MRI Segmentation,”Medical Imaging VI: Image Processing, 1652:668-677, 1992.
Taxt et al., “Multispectral Analysis of Uterine Corpus Tumors in Magnetic Resonance Imaging,”Magnetic Resonance in Medicine, 23:55-76, 1992.
Bezdek et al., “Review of MR Image Segmentation Techniques Using Pattern Recognition,”Medical Physics, 20(4):1033-1048, 1993.
Taxt et al., “Multispectral Analysis of the Brain Using Magnetic Resonance Imaging,”IEEE Transactions on Medical Imaging, 13(3):470-481, 1994.
Clarke et al., “MRI Segmentation: Methods and Applications,”Magnetic Resonance Imaging, 13(3):343-368, 1995.
Dasarathy “Adaptive Decision Systems with Extended Learning for Deployment in Partially Exposed Environments,”Optical Engineering, 34(5):1269-1280, 1995.
Pham et al., “Partial Volume Estimation and the Fuzzy C-means Algorithm,” 4 pages.
Mussurakis et al., “Dynamic MRI of Invasive Breast Cancer: Assessment of Three Region-of-Interest Analysis Methods.”Journal of Computer Assisted Tomography, 21(3):431-438, 1997.
Samarasekera et al., “A New Computer-Assisted Method for the Quantification of Enhancing Lesions in Multiple Sclerosis,”Journal of Computer Assisted Tomography, 21(1):145-151, 1997.
“Spatial Filtering,” Digital Image Processing 4.3, pp. 189-195.
Clark et al., “Automatic Tumor Segmentation Using Knowledge-Based Techniques,”IEEE Transactions on Medical Imaging, 17(2):187-201, 1998.
Clark et al., “MRI Measurement of Brain Tumor Response: Comparison of Visual Metric and Automatic Segmentation,”Magnetic Resonance Imaging, 16(3):271-279, 1998.
Houben et al., “Distance Rejection in the Context of Electric Power System Security Assessment Based on Automatic Learning,” inProceedings of Advances in Pattern Recognition: Joint lAPR International Workshops SSPR '98 and SPR '98, Sydney, Australia, 1998, pp. 756-764.
Parker et al., “MRIW: Parametric Analysis Software for Contrast-Enhanced Dynamic MR Imaging in Cancer,”RadioGraphics, 18(2):497-506, 1998.
Reiss et al., “Reliability and Validity of an Algorithm for Fuzzy Tissue Segmentation of MRI,”Journal of Computer Assisted Tomography, 22(3):471-479, 1998.
Weinstein et al., “Breast Fibroadenoma: Mapping of Pathophysiologic Features with Three-Time-Point, Contrast-Enhanced MR Imaging—Pilot Study,”Radiology, 210(1):233-240, 1999.
Kuhl et al., “Dynamic Breast MR Imaging: Are Signal Intensity Time Course Data Useful for Differential Diagnosis of Enhancing Lesions?,”Radiology, 211(1):101-110, 1999.
Orel, “Differentiating Benign from Malignant Enhancing Lesions Identified at MRI Imaging of the Breast: Are Time-Signal Intensity Curves an Accurate Predictor?,”Radiology, 211(1):5-7, 1999.
Liney et al., “Dynamic Contrast-Enhanced MRI in the Differentiation of Breast Tumors: User-Defined Versus Semi-Automated Region-of-Interest Analysis,”Journal of Magnetic Resonance Imaging10:945-949, 1999.
Hylton, “Vascularity Assessment of Breast Lesions with Gadolinium-Enhanced MR Imaging,”MRI Clinics of North America, 9(2):321-331, 2001.
Hylton, “Vascularity Assessment of Breast Lesions with Gandolinium-Enhanced MR Imaging,”MRI Clinics of North America 7(2):411-420, May 1999.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Rules-based approach for processing medical images does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Rules-based approach for processing medical images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Rules-based approach for processing medical images will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3842091

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.