US5625705A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Intensity texture based classification system and method
Assignee: AutoCyte North Carolina LLC
•
Filing: 1994-06-03
•
Granted: 1997-04-29
•
Expires: 2014-06-03
Abstract
Abstract A method for classifying objects within a specimen as likely to be premalignant or malignant cells includes the steps of forming an intensity image of a specimen, calculating and storing the maximum and minimum grey scale values at a plural number of distances from a pixel in the intensity image, finding the difference between the maximum and minimum grey scale values at like distances from the pixel, determining the slope of the log of the differences as a function of the log of the distances, storing the slope at the pixel location in a resultant image, and identifying objects in the intensity image as likely to be malignant or premalignant based on the value of the slope.
Inventors
- 👤 Joel M. Recht
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 14:29
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/0002; G06T7/0012; G06T7/40; G06T7/41; G06T7/48; G06V; G06V20/00; G06V20/60; G06V20/69; G06V20/695; G06T2207/00; G06T2207/10; G06T2207/10056; G06T2207/30; G06T2207/30004; G06T2207/30024
Claims Analysis
Total Claims: 15
Claim 1
Independent Claim
133 words
A method for classifying objects within a specimen as likely to be premalignant or malignant cells, comprising the steps of: a) forming an intensity image of at least part of a specimen using a microscope; b) using a processing element to find and store the maximum and minimum grey scale values at plural distances from a pixel in said intensity image; c) finding the difference between the maximum and minimum grey scale values at the respective distances from said pixel using an algorithmic logic unit; d) determining the slope of the log of said differences as a function of the log of said distances to provide a measure of intensity texture; and e) classifying objects in said intensity image as likely to be malignant or premalignant based on the value of said slope.
Claim 2
Independent Claim
133 words
A method for classifying objects within a specimen as likely to be premalignant or malignant cells, comprising the steps of: a) forming an intensity image of at least part of a specimen using a microscope; b) using a processing element to find and store the maximum and minimum grey scale values at plural distances from a pixel in said intensity image; c) finding the difference between the maximum and minimum grey scale values at the respective distances from said pixel using an algorithmic logic unit; d) determining the slope of the log of said differences as a function of the log of said distances to provide a measure of intensity texture; and e) classifying objects in said intensity image as likely to be malignant or premalignant based on the value of said slope.
Claim 3
Dependent Claim
18 words
The method of claim 1, wherein said step of determining the slope includes using a least squares fit.
Claim 4
Dependent Claim
20 words
The method of claim 1, wherein said step of determining the slope includes using a two value look up table.
Claim 5
Dependent Claim
14 words
The method of claim 1, including determining the Hurst coefficient based on said slope.
Claim 6
Dependent Claim
15 words
The method of claim 1, wherein said step of classifying includes using a neural network.
Claim 7
Dependent Claim
36 words
The method of claim 1, including forming a resultant image based on said slopes and masking out information in said resultant image which does not correspond to the location of cell nuclei in the intensity image.
Claim 8
Independent Claim
139 words
A method for classifying objects based on surface texture, comprising the steps of: a) forming an intensity image of at least part of the surface of the object using a camera; b) using a hardware ranker to find the maximum and minimum grey scale values at plural distances from each pixel in said intensity image; c) subtracting the minimum grey scale values from the maximum grey scale values at the respective distances from each said pixel using an algorithmic logic unit; d) looking up the slope of the log of said differences as a function of the log of said distances in a look up table for each said pixel to provide a measure of intensity texture; and e) classifying objects in said intensity image as likely to have a certain characteristic based on the values of said slopes.
Claim 9
Independent Claim
139 words
A method for classifying objects based on surface texture, comprising the steps of: a) forming an intensity image of at least part of the surface of the object using a camera; b) using a hardware ranker to find the maximum and minimum grey scale values at plural distances from each pixel in said intensity image; c) subtracting the minimum grey scale values from the maximum grey scale values at the respective distances from each said pixel using an algorithmic logic unit; d) looking up the slope of the log of said differences as a function of the log of said distances in a look up table for each said pixel to provide a measure of intensity texture; and e) classifying objects in said intensity image as likely to have a certain characteristic based on the values of said slopes.
Claim 10
Independent Claim
127 words
A system for classifying objects based on surface texture, comprising: a camera which obtains an intensity image of at least part of the surface of the object; a ranker which finds the maximum and minimum grey scale values at plural distances from each pixel in said intensity image; an arithmetic logic unit which subtracts the minimum grey scale values from the maximum grey scale values at the respective distances from each said pixel; a lookup table containing the slope of the log of said differences as a function of the log of said distances, the slope for providing a measure of intensity texture; and a classifier for classifying objects in said intensity image as likely to have a certain characteristic based on the values of said slopes.
Claim 11
Independent Claim
127 words
A system for classifying objects based on surface texture, comprising: a camera which obtains an intensity image of at least part of the surface of the object; a ranker which finds the maximum and minimum grey scale values at plural distances from each pixel in said intensity image; an arithmetic logic unit which subtracts the minimum grey scale values from the maximum grey scale values at the respective distances from each said pixel; a lookup table containing the slope of the log of said differences as a function of the log of said distances, the slope for providing a measure of intensity texture; and a classifier for classifying objects in said intensity image as likely to have a certain characteristic based on the values of said slopes.
Claim 12
Dependent Claim
16 words
The system of claim 8, wherein said lookup table is a two value look up table.
Claim 13
Dependent Claim
13 words
The system of claim 8, including a plurality of two value lookup tables.
Claim 14
Dependent Claim
11 words
The system of claim 8, wherein said classifier includes a neurocomputer.
Claim 15
Dependent Claim
13 words
The method of claim 1, wherein the processing element includes a hardware ranker.
References Cited (Backward Citations)
US4207554A
Cited
US4618937A
Cited
US4661913A
Cited
US4853777A
Cited
US5287272A
Cited
US4965725A
Cited
US5287272B1
Cited
US4965725B1
Cited
US5107422A
Cited
US5117293A
Cited
US5194949A
Cited
US5103306A
Cited
US5333207A
Cited
US5257182B1
Cited
US5257182A
Cited
US5353061A
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2000-04-28 | 2000-10-28 | 2001-04-29 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2004-04-28 | 2004-10-28 | 2005-04-29 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2008-04-28 | 2008-10-28 | 2009-04-29 | $7700.00 | Window Closed / Lapsed |