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Patent US6674880B1 successfully refreshed from Google Patents.
US6674880B1
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Convolution filtering of similarity data for visual display of enhanced image
Assignee: Merative US LP
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Filing: 2000-11-24
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Granted: 2004-01-06
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Expires: 2020-11-24
Abstract
Abstract A similarity value of data elements is modified to provide an improved image of an object. Using an appropriate sensor, data is collected from an object and stored as a plurality of discrete data points. The data points are compared to each other to determine how similar the data properties of one data element are to another data element. A similarity value is assigned to each of the data elements representative of the difference between the properties of the two data elements. The similarity value for each particular data element is then modified based on a weighted similarity value of the data element itself and a group of adjacent data elements. The modified similarity value is then stored for each data element and used to produce an image representative of the object.
Inventors
- 👤 Christopher L. Stork
- 👤 Bradley T. Wyman
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-01 08:28
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/0002; G06T7/0012; G06T2207/00; G06T2207/30; G06T2207/30004
Claims Analysis
Total Claims: 15
Claim 1
Independent Claim
147 words
A method of modifying data, comprising: storing in a first memory the representation of an object using a plurality of discrete data elements that represent corresponding locations in the object; assigning a similarity value to each data element, the value of the similarity being representative of a property of the object; organizing the similarity values of the discrete data elements into a pattern in which data elements that are adjacent to each other in the pattern represent adjacent locations within the object; modifying the similarity value of a selected data element based on the weighted similarity value of itself and a plurality of adjacent data elements; storing the modified similarity values of the data elements; and forming an image viewable by a user that is composed of a plurality of discrete visual pixels whose display properties are based on the modified similarity values of the data elements.
Claim 2
Independent Claim
147 words
A method of modifying data, comprising: storing in a first memory the representation of an object using a plurality of discrete data elements that represent corresponding locations in the object; assigning a similarity value to each data element, the value of the similarity being representative of a property of the object; organizing the similarity values of the discrete data elements into a pattern in which data elements that are adjacent to each other in the pattern represent adjacent locations within the object; modifying the similarity value of a selected data element based on the weighted similarity value of itself and a plurality of adjacent data elements; storing the modified similarity values of the data elements; and forming an image viewable by a user that is composed of a plurality of discrete visual pixels whose display properties are based on the modified similarity values of the data elements.
Claim 3
Dependent Claim
27 words
The method according to claim 1 wherein all data elements that are located within three data elements of the selected data element are considered to be adjacent.
Claim 4
Dependent Claim
27 words
The method according to claim 1 wherein all data elements that are located within two data elements of the selected data elements are considered to be adjacent.
Claim 5
Dependent Claim
33 words
The method according to claim 1 wherein the weighted value of one adjacent data element compared to another adjacent data element is based on a gaussian pattern of weighting of the data elements.
Claim 6
Dependent Claim
93 words
The method according to claim 1 wherein the step of modifying the value of the selected pixel comprises: forming a convolution kernel having the selected pixel and the plurality of adjacent pixels therein; multiplying the similarity value of the selected pixel and the adjacent pixels by the weighted value of each pixel in the convolution kernel to obtain a set of first products; summing the products of all pixels in the convolution kernel to obtain a weighted similarity value; and storing the similarity value of the selected pixel with the weighted similarity value.
Claim 7
Dependent Claim
17 words
The method according to claim 5 wherein the sum of all weighted factors is equal to one.
Claim 8
Dependent Claim
46 words
The method according to claim 1 , further including: forming a training set of data elements; forming a testing set of data elements; and comparing each test data element to the training set of data elements to obtain a similarity value for the test data element.
Claim 9
Dependent Claim
35 words
The method according to claim 1 , further including: storing the similarity value of each data element in a first memory; and storing the modified similarity values of the data elements in a second memory.
Claim 10
Dependent Claim
36 words
The method according to claim 1 wherein said step of organizing the similarity values of the discrete data elements is carried out by organizing the storage location of the discrete data elements in the first memory.
Claim 11
Dependent Claim
43 words
The method according to claim 1 further including creating a binary image of the MR data comprising: setting a threshold for the similarity value; creating a class of data elements, including all data elements having a similarity value greater than the threshold value.
Claim 12
Dependent Claim
41 words
The method according to claim 10 further including: displaying, as a single color, all pixels representative of data elements within the selected class; and displaying pixels not within the selected class using a different color than those within the selected class.
Claim 13
Dependent Claim
28 words
The method according to claim 11 wherein the color selected is one color within a gray scale color scheme, the entire image being shown on a gray scale.
Claim 14
Dependent Claim
42 words
The method according to claim 11 wherein the color selected for the class of interest is black and all other tissues are shown on a gray scale pattern having a color different from black which are not within the class of interest.
Claim 15
Dependent Claim
41 words
The method according to claim 11 wherein the color selected is from the spectrum of colors visible to the human eye and pixels representing tissue not in the class of interest are displayed using a different color in the color spectrum.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2007-01-05 | 2007-07-07 | 2008-01-06 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2011-01-05 | 2011-07-07 | 2012-01-06 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2015-01-05 | 2015-07-07 | 2016-01-06 | $7700.00 | Window Closed / Lapsed |