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| Arrangement for mapping colors between imaging systems and method therefor |
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| Image processing method and apparatus |
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| Image processing apparatus and method, and profile generating method |
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Method and system for knowledge guided hyperintensity detection and volumetric measurement
| Details |
Inventors: Gosche, Karen M.;
Assignee: University of South Florida (Tampa, FL)
Primary Examiner: Lateef; Marvin M.
Assistant Examiner: James; Ialaya G
Attorney, Agent or Firm: Katten Muchin Zavis Rosenman
An automated method and/or system for identifying suspected lesions in a brain is provided. A processor (a) provides a magnetic resonance image (MRI) of a patient's head, including a plurality of slices of the patient's head, which MRI comprises a multispectral data set that can be displayed as an image of varying pixel intensities. The processor (b) identifies a brain area within each slice to provide a plurality of masked images of intracranial tissue. The processor (c) applies a segmentation technique to at least one of the masked images to classify the varying pixel intensities into separate groupings, which potentially correspond to different tissue types. The processor (d) refines the initial segmentation into the separate groupings of at least the first masked image obtained from step (c) using one or more knowledge rules that combine pixel intensities with spatial relationships of anatomical structures to locate one or more anatomical regions of the brain. The processor (e) identifies, if present, the one or more anatomical regions of the brain located in step (d) in other masked images obtained from step (c). The processor (f) further refines the resulting knowledge rule-refined images from steps (d) and (e) to locate suspected lesions in the brain. |
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DETAILED DESCRIPTION It is, therefore, a feature and advantage of the present invention to provide a method and/or system for detecting hyperintense regions in MRI images which addresses the problems associated with human subjectivity and existing thresholding techniques.
In particular, the present invention introduces the concept of the use of knowledge guided rules and methods for automatically locating certain anatomical regions and detecting hyperintensities associated with same, which in turn are candidates for possible lesions.
It is another feature and advantage of the present invention to provide a method and/or system for detecting white matter hyperintensities and subcortical hyperintensity regions in MRI images which is designed for high sensitivity, detection and monitoring of subtle (small) brain lesions in patients with neurodegenerative diseases.
It is also a feature and advantage of the present invention to provide an automated method and/or automated system for detecting hyperintensities in MRI images which requires no a priori knowledge of the intensity distributions of image pixels and which does not require any additional direction from an expert operator to perform its task.
Yet another feature and advantage of the present invention is to provide a method and/or system for processing the information and/or data provided by MRI images to detect and identify hyperintensities for disease screening, and thereby serve as a diagnostic aid in helping neuroradiologists verify disease diagnosis and severity, to arrive at a prognosis, or to follow the possible effects of therapy (e.
g.
, drug therapy).
The above features and advantages are accomplished, for example, by an automated, knowledge-guided hyperintensity detection (KGHID) method or system that uses encoded knowledge of brain anatomy and MRI characteristics of individual tissues to reclassify pixels from an initial unsupervised tissue classification.
The method/system herein described optionally requires no more than a reliable initial segmentation of brain tissues into classes of, for example, cerebral spinal fluid, white matter, gray matter and mixed boundary tissue
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Image Analysis 
