US2018068454A1PendingUtilityA1
Simultaneous segmentation and grading of structures for state determination
Est. expirySep 16, 2031(~5.1 yrs left)· nominal 20-yr term from priority
G06T 7/33A61B 5/055G06T 7/0012G06T 2207/10088A61B 5/0042G06T 2207/30016A61B 5/4088G06T 7/41
48
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Claims
Abstract
Applicants have discovered a new low-cost and accessible method and apparatus that allowing for quicker and more precise state determinations based on medical images. The method and apparatus are non-intrusive and require providing a medical image of a subject and determining a state based on a comparison to a training image set comprising two or more states. There is provided, according to the present invention, a computer-implemented method for processing medical images comprising calculating non-local means patch-based weights comparing patches surrounding pixels of interest in a test image with a number of patches of pixels surrounding a corresponding number of pixels in reference images; and calculating for the pixels of interest at least one state estimation using a given state assigned to said reference images and said weights.
Claims
exact text as granted — not AI-modified1 . A computer-implemented method for processing medical images, the method comprising: calculating in a processor non-local means patch-based weights comparing patches surrounding pixels of interest in a test image with a number of patches of pixels surrounding a corresponding number of pixels in reference images; and calculating in a processor for said pixels of interest at least one state estimation using a given state assigned to said reference images and said weights.
2 . The method as claimed in claim 1 , wherein said pixels of interest define a region of interest of said test image, said region of interest comprising a structure that changes with said state.
3 . The method as claimed in claim 1 , wherein said state is a likelihood of progressing from mild cognitive impairment to Alzheimer's disease.
4 . The method as claimed in claim 1 , wherein a reference patch used in said calculating is selected according to its relatedness to a test patch surrounding said pixels of interest.
5 . The method as claimed in claim 4 , wherein said relatedness is determined by a mean and a standard deviation of intensity values of said test patch pixels and said reference patch pixels.
6 . (canceled)
7 . The method as claimed in claim 1 , wherein said state estimation comprises a structure label value for each pixel of said reference images, and said method provides segmentation of said test image structure.
8 . The method as claimed in claim 1 , wherein a sequential series of images in space allows to determine a volume of said structure.
9 . The method as claimed in claim 1 , wherein said state estimation comprises a pathological state of patients related to said reference images, and said method provides pathological state grading of said pixels of interest in said test image.
10 . The method as claimed in claim 1 , wherein said state estimation comprises a pathological state of patients related to said reference images, and said method provides segmentation and pathological state grading of said pixels of interest in said test image.
11 . The method as claimed in claim 9 , further comprising calculating a pathological state score from said grading of said pixels of interest.
12 . The method as claimed in claim 9 , further comprising calculating a pathological state score from said grading of said pixels of interest having a predetermined segmentation.
13 . The method as claimed in claim 1 , wherein said calculating said state estimation comprises using the formula:
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where
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and g(x i ) is a grade, N is a number of subjects, w is a weight, p s is a state, P is a patch surrounding a pixel, X i is the pixel of interest of the test image, X s,j is a pixel in a reference image and h 2 is a smoothing function.
14 . The method as claimed in claim 2 , wherein said state of being said structure is calculated using a formula:
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where I is a label (0 for non-structure and 1 for structure) and a pixel v(xi) is segmented as structure when v(x i ) is greater than 0.5.
15 . The method of claim 1 , wherein a state associated with a reference image of a reference subject is changed when the state of said reference subject changes.
16 . The method of claim 1 , wherein said test image becomes a reference image when the state of the subject becomes known.
17 . The method of claim 1 , wherein said state is calculated using a grade of said structure and a volume of said structure.
18 . The method of claim 2 , wherein said structure comprises one or more of a left hippocampus, a right hippocampus, a left entorhinal cortex, a right entorhinal cortex.
19 . The method of claim 1 , wherein said patch size is between 1.times.1.times.1voxels and 100.times.100.times.100 voxels.
20 - 27 . (canceled)
28 . The method of claim 2 , wherein said state estimation of pixels of interest are averaged to provide a state of a structure of interest.
29 . The method of claim 1 , further comprising matching said test image subject's age with reference image subjects' age to increase a classification efficiency.
30 . The method of claim 1 , further comprising matching said test image subject's MMSE score with reference image subjects' MMSE score to increase a classification efficiency.
31 . An apparatus for processing medical images comprising: a non-local means patch-based weight calculator for calculating a weight of a pixel of interest in a test image with a number of patches of pixels surrounding a corresponding number of pixels in a reference image; and a state calculator for calculating a state of said pixel of interest based on a given state assigned to said reference image.
32 - 40 . (canceled)
41 . A system for processing medical images comprising: a medical imager for generating a test image; an apparatus configured to implement the method of claim 1 ; a client application for receiving and presenting data provided by said apparatus; wherein said imager, apparatus and client application communicate data over a network and return to said client application a pathological state determination.
42 . The method of claim 1 , further comprises processing a medical image of a brain of a subject with mild cognitive impairment to determine whether the subject has progressive or stable mild cognitive impairment.
43 . The method of claim 42 , wherein a success rate of said determining is greater than 70%.
44 . (canceled)Join the waitlist — get patent alerts
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