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US4965725A
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Neural network based automated cytological specimen classification system and method
Assignee: TriPath Imaging Inc
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Filing: 1988-04-08
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Granted: 1990-10-23
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Expires: 2008-04-08
Abstract
Abstract An automated screening system and method for cytological specimen classification in which a neural network is utilized in performance of the classification function. Also included is an automated microscope and associated image processing circuitry.
Inventors
- 👤 Mark R. Rutenberg
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-25 21:09
CPC Classifications
G; G06; G06V; G06V20/00; G06V20/60; G06V20/69; G06V20/693; G01; G01N; G01N15/00; G01N15/10; G01N15/14; G01N15/1468; G06N; G06N3/00; G06N3/02; G06N3/04; G06N3/0499; G06N3/08; G06N3/09; G06V20/698; G16; G16H; G16H30/00; G16H30/40; G16H50/00; G16H50/20; G01N15/1429; G01N15/1433; G01N2015/1488; Y; Y10; Y10S; Y10S128/00; Y10S128/92; Y10S128/925; Y10S706/00; Y10S706/902; Y10S706/924
Claims Analysis
Total Claims: 46
Claim 1
Independent Claim
198 words
An automated cytological specimen classifier for classifying cells contained in a smear on a slide to identify cells that are likely to be malignant or pre-malignant, comprising: (a) microscope means for obtaining a vie of at least part of a cytological specimen including cells and other material located generally randomly on a slide in an arrangement which can include other than a single layer of cells, (b) camera means for creating an image of such view, (c) image digitizing means for producing a digital representation of such image, (d) a primary classifier means for detecting objects in a digital representation of a cytological specimen based on a detectable feature, said primary classifier means comprising a classifier means for detecting cells that are likely to be malignant or pre-malignant as well as other cells and material that initially appear to have characteristics of a malignant cell or a pre-malignant cell based on integrated optical density, and (e) a secondary classifier for distinguishing pre-malignant and malignant cells form other cells and material among the objects detected by the primary classifier, said secondary classifier means comprising a neural computer apparatus means for effecting such distinguishing as a function of training thereof.
Claim 2
Dependent Claim
198 words
An automated cytological specimen classifier for classifying cells contained in a smear on a slide to identify cells that are likely to be malignant or pre-malignant, comprising: (a) microscope means for obtaining a vie of at least part of a cytological specimen including cells and other material located generally randomly on a slide in an arrangement which can include other than a single layer of cells, (b) camera means for creating an image of such view, (c) image digitizing means for producing a digital representation of such image, (d) a primary classifier means for detecting objects in a digital representation of a cytological specimen based on a detectable feature, said primary classifier means comprising a classifier means for detecting cells that are likely to be malignant or pre-malignant as well as other cells and material that initially appear to have characteristics of a malignant cell or a pre-malignant cell based on integrated optical density, and (e) a secondary classifier for distinguishing pre-malignant and malignant cells form other cells and material among the objects detected by the primary classifier, said secondary classifier means comprising a neural computer apparatus means for effecting such distinguishing as a function of training thereof.
Claim 3
Dependent Claim
15 words
The automated classifier of claim 1 wherein said primary classifier means comprises a statistical classifier.
Claim 4
Dependent Claim
13 words
The automated classifier of claim 1 wherein such cytological specimen includes overlapping cells.
Claim 5
Dependent Claim
27 words
The automated classifier of claim 1 wherein said secondary classifier means is operable to distinguish pre-malignant and malignant cells among overlapping arrangements of cells and other material.
Claim 6
Dependent Claim
26 words
The automated classifier of claim 1, wherein said camera means is positioned to create an image of a portion of such cytological specimen from such view.
Claim 7
Dependent Claim
16 words
The automated classifier of claim 1, said neural computer apparatus means comprising an electronic neural computer.
Claim 8
Dependent Claim
33 words
The automated classifier of claim 1 wherein the primary classifier means is restricted to evaluation of the cellular nucleus while the secondary classifier means evaluates both the cellular nucleus and its surrounding cytoplasm.
Claim 9
Dependent Claim
25 words
The automated classifier of claim 1 wherein both the primary classifier means and the secondary classifier means are restricted to evaluation of the cellular nucleus.
Claim 10
Dependent Claim
40 words
The automated classifier of claim 1 further comprising means for making an additional non-neural net classification of nuclear morphological components in addition to integrated optical density, said means being coupled between the primary classifier means and the secondary classifier means.
Claim 11
Dependent Claim
13 words
The automated classifier of claim 1, said microscope means comprising an automated microscope.
Claim 12
Dependent Claim
13 words
The automated classifier of claim 1, said camera means comprising a video camera.
Claim 13
Dependent Claim
14 words
The automated classifier of claim 1, said camera means comprising a charge coupled device.
Claim 14
Dependent Claim
33 words
The automated classifier of claim 1, said primary classifier means comprising means for detection of objects in such digital representation of a cytological specimen which has a feature that exceeds a threshold level.
Claim 15
Dependent Claim
35 words
The automated classifier of claim 1, said primary classifier means comprising means for detection of objects in such digital representation of a cytological specimen which has a feature that exceeds a threshold integrated optical density.
Claim 16
Dependent Claim
28 words
The automated classifier of claim 1, said primary classifier means comprising means for detection of objects in such digital representation of a cytological specimen based on morphological criteria.
Claim 17
Dependent Claim
45 words
The automated classifier of claim 1 further comprising a neural network pre-screening classifier means for recognition and classification of general areas within the digital representation of a specimen that contain material other than a cellular monolayer prior to primary classification by said primary classifier means.
Claim 18
Dependent Claim
23 words
The automated classifier of claim 16 wherein the output form the pre-screening classifier means is utilized to exclude such areas from further analysis.
Claim 19
Dependent Claim
26 words
The automated classifier of claim 16 wherein the output form the pre-screening classifier means is utilized to modify further analysis of images found within such areas.
Claim 20
Independent Claim
48 words
A method of classifying cytological specimens, comprising using a primary classifier apparatus primarily classifying a specimen which is generally randomly arranged and can include other than in a single layer to determine locations of interest, and secondarily classifying such locations of interest using a neural network computer apparatus.
Claim 21
Independent Claim
48 words
A method of classifying cytological specimens, comprising using a primary classifier apparatus primarily classifying a specimen which is generally randomly arranged and can include other than in a single layer to determine locations of interest, and secondarily classifying such locations of interest using a neural network computer apparatus.
Claim 22
Dependent Claim
38 words
The method of claim 19, wherein said primarily classifying step comprises using a video camera or charge coupled device (CCD) to obtain images of the specimen, a digitizer to digitize such images and an integrated optical density detector.
Claim 23
Dependent Claim
16 words
The method of claim 19, wherein said primary classifying comprises using a neural network computer apparatus.
Claim 24
Dependent Claim
23 words
The method of claim 19, wherein said step of using a primary classifier apparatus primarily classifying a specimen comprises using a statistical classifier.
Claim 25
Dependent Claim
25 words
The method of claim 19, wherein said step of using a primary classifier apparatus primarily classifying a specimen comprises making a classification based on morphology.
Claim 26
Dependent Claim
28 words
The method of claim 19, wherein said step of using a primary classifier apparatus primarily classifying a specimen comprises making such primary classification based on integrated optical density.
Claim 27
Dependent Claim
19 words
The method of claim 19, further comprising training such neural network computer apparatus to identify cytological specimens of interest.
Claim 28
Dependent Claim
169 words
An automated cytological specimen classifier, comprising: (a) microscope means for obtaining a view of at least part of a cytological specimen including cells and other material located generally randomly in an arrangement which can include other than a single layer of cells, (b) camera means for creating an image of such view, (c) image digitizing means for producing a digital representation of such image, (d) primary classifier means for detecting objects in a digital representation of a cytological specimen based on a detectable feature, said primary classifier means comprising a classifier for detecting cells that are likely to be of a predetermined cell type as well as other cells and material that initially appear to have characteristics of such predetermined cell type, and (e) secondary classifier means for distinguishing cells of such predetermined cell type from other cells and material among the objects detected by said primary classifier means, said secondary classifier means comprising a neural computer apparatus means for effecting such distinguishing as a function of training thereof.
Claim 29
Dependent Claim
169 words
An automated cytological specimen classifier, comprising: (a) microscope means for obtaining a view of at least part of a cytological specimen including cells and other material located generally randomly in an arrangement which can include other than a single layer of cells, (b) camera means for creating an image of such view, (c) image digitizing means for producing a digital representation of such image, (d) primary classifier means for detecting objects in a digital representation of a cytological specimen based on a detectable feature, said primary classifier means comprising a classifier for detecting cells that are likely to be of a predetermined cell type as well as other cells and material that initially appear to have characteristics of such predetermined cell type, and (e) secondary classifier means for distinguishing cells of such predetermined cell type from other cells and material among the objects detected by said primary classifier means, said secondary classifier means comprising a neural computer apparatus means for effecting such distinguishing as a function of training thereof.
Claim 30
Dependent Claim
33 words
The automated classifier of claim 16, wherein the primary classifier means is restricted to evaluation of the cellular nucleus while the secondary classifier means evaluates both the cellular nucleus and its surrounding cytoplasm.
Claim 31
Dependent Claim
25 words
The automated classifier of claim 26 wherein both the primary classifier means and the secondary classifier means are restricted to evaluation of the cellular nucleus.
Claim 32
Dependent Claim
34 words
The automated classifier of claim 26, further comprising means for making an additional non-neural net classification of nuclear morphological components, said means being coupled between the primary classifier means and said secondary classifier means.
Claim 33
Dependent Claim
13 words
The automated classifier of claim 26, said microscope means comprising an automated microscope.
Claim 34
Dependent Claim
13 words
The automated classifier of claim 16, said camera means comprising a video camera.
Claim 35
Dependent Claim
14 words
The automated classifier of claim 26, said camera means comprising a charge coupled device.
Claim 36
Dependent Claim
33 words
The automated classifier of claim 26, said primary classifier means comprising means for detection of objects in such digital representation of a cytological specimen which have a feature that exceeds a threshold level.
Claim 37
Dependent Claim
35 words
The automated classifier of claim 26, said primary classifier means comprising means for detection of objects in such digital representation of a cytological specimen which has a feature that exceeds a threshold integrated optical density.
Claim 38
Dependent Claim
28 words
The automated classifier of claim 26, said primary classifier means comprising means for detection of objects in such digital representation of a cytological specimen based on morphological criteria.
Claim 39
Dependent Claim
26 words
The automated classifier of claim 26, wherein said camera means is positioned to create an image of a portion of such cytological specimen from such view.
Claim 40
Dependent Claim
16 words
The automated classifier of claim 26, said neural computer apparatus means comprising an electronic neural computer.
Claim 41
Dependent Claim
14 words
The automated classifier of claim 16 wherein primary classifier means comprises a statistical classifier.
Claim 42
Dependent Claim
13 words
The automated classifier of claim 16 wherein such cytological specimen includes overlapping cells.
Claim 43
Dependent Claim
29 words
The automated classifier of claim 16 wherein said secondary classifier means is operable to distinguish cells of such predetermined cell type among overlapping arrangements of cells and other materials.
Claim 44
Dependent Claim
37 words
The automated classifier of claim 26 further comprising a neural network pre-screening classifier means for identifying general areas within the digital representation of a specimen that contain material other than a cellular monolayer prior to primary classification.
Claim 45
Dependent Claim
23 words
The automated classifier of claim 41 wherein the output from the pre-screening classifier is utilized to exclude such identified areas from further analysis.
Claim 46
Dependent Claim
35 words
The automated classifier of claim 41 wherein the output from the pre-screening classifier means is utilized to modify further analysis of images found within the areas of the specimen identified by said pre-screening classifier means.
References Cited (Backward Citations)
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 1993-10-22 | 1994-04-23 | 1994-10-23 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 1997-10-22 | 1998-04-23 | 1998-10-23 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2001-10-22 | 2002-04-23 | 2002-10-23 | $7700.00 | Window Closed / Lapsed |