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US5838815A Expired / Lapsed US ⏱️ 0.0 years remaining

Method and system to enhance robust identification of abnormal regions in radiographs

Assignee: University of Pittsburgh
•
Filing: 1996-02-22
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Granted: 1998-11-17
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Expires: 2016-02-22
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Abstract

Abstract A method and apparatus for detecting abnormal regions in living tissue depicted in a digital radiograph includes identifying suspected abnormal regions depicted in the radiograph and then, for each identified suspected abnormal region, extracting multiple topographic layers of the region from the digital radiograph; determining features of the region in each of the layers; and applying inter-layer multivariate non-linear criteria to the features to determine whether the suspected abnormal region is to be classified as an abnormal region. The distribution of digital values in the digitized radiograph is modified and a probabalistic determination is made as to whether suspected abnormal regions are actually abnormal from multiple analyses. An image is processed using at least two partially correlated detection schemes to produce at least two corresponding result sets of potentially abnormal regions; and the results of the detection schemes are combined using logical "AND" or logical "OR" combining rules to detect abnormal regions in the radiograph.

Inventors

  • 👤 David Gur
  • 👤 Bin Zheng
  • 👤 Yuan-Hsiang Chang

Bibliographic Details

Application Number —
Jurisdiction US
Data Source google_patents
Last Synchronized 2026-11-09 22:15
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/0002; G06T7/0012; G06V; G06V20/00; G06V20/60; G06V20/69

Claims Analysis

Total Claims: 26
Claim 1
Independent Claim 80 words
A method of detecting an abnormal region in living tissue depicted in a digital radiograph, the method comprising: identifying a suspected abnormal region depicted in the radiograph; extracting multiple topographic layers of the suspected abnormal region from the digital radiograph, the multiple topographic layers being extracted from the same radiograph; determining features of the region in each of said layers; and applying an inter-layer multivariate criterion to said features to determine whether said suspected abnormal region is an abnormal region.
Claim 2
Independent Claim 80 words
A method of detecting an abnormal region in living tissue depicted in a digital radiograph, the method comprising: identifying a suspected abnormal region depicted in the radiograph; extracting multiple topographic layers of the suspected abnormal region from the digital radiograph, the multiple topographic layers being extracted from the same radiograph; determining features of the region in each of said layers; and applying an inter-layer multivariate criterion to said features to determine whether said suspected abnormal region is an abnormal region.
Claim 3
Dependent Claim 11 words
A method as in claim 1, wherein said criterion is non-linear.
Claim 4
Dependent Claim 64 words
A method as in claim 1, wherein said features of the region include at least one of: the size of the region, the shape of the region, the longest axis of the region; the contrast of the region; the standard deviation of the region; the skewness of the region; the size growth ratio of the region; and the central position shift of the region.
Claim 5
Dependent Claim 209 words
A method as in claim 3, wherein said criterion relates to at least one of: (a) the contrast and the standard deviation in a third layer; (b) the shape factor and longest axis in the third layer; (c) the size and the contrast in a first layer; (d) the growth ratio between the first layer and a second layer compared to the growth ratio between the second and third layers; (e) the shape factor in the second layer and the central position shift between the first and second layers; (f) the contrast in the first layer and central position shift between the first and second layer; (g) the growth ratio between the second and third layers compared to the skewness in the second layer; (h) the growth ratio between the second and third layers compared to the standard deviation in the first layer; (i) the shape factor in the second layer compared to the skewness in the third layer; (j) the shape factor in the second layer compared to the shape factor in the third layer; (k) the standard deviation in the first layer compared to the longest axis in the second layer; and (l) the contrast in the first layer compared to the skewness in the second layer.
Claim 6
Dependent Claim 60 words
A method as in claim 2, wherein said features of the region include: the size of the region, the shape of the region, the longest axis of the region; the contrast of the region; the standard deviation of the region; the skewness of the region; the size growth ratio of the region; and the central position shift of the region.
Claim 7
Dependent Claim 205 words
A method as in claim 5, wherein said criterion relates to: (a) the contrast and the standard deviation in a third layer; (b) the shape factor and longest axis in the third layer; (c) the size and the contrast in a first layer; (d) the growth ratio between the first layer and a second layer compared to the growth ratio between the second and third layers; (e) the shape factor in the second layer and the central position shift between the first and second layers; (f) the contrast in the first layer and central position shift between the first and second layer; (g) the growth ratio between the second and third layers compared to the skewness in the second layer; (h) the growth ratio between the second and third layers compared to the standard deviation in the first layer; (i) the shape factor in the second layer compared to the skewness in the third layer; (j) the shape factor in the second layer compared to the shape factor in the third layer; (k) the standard deviation in the first layer compared to the longest axis in the second layer; and (l) the contrast in the first layer compared to the skewness in the second layer.
Claim 8
Dependent Claim 55 words
A method as in claim 3, wherein said criterion relates to at least one of: the contrast and the standard deviation in a third layer; the shape factor in a second layer compared to the skewness in the third layer; and the contrast in a first layer compared to the skewness in the second layer.
Claim 9
Dependent Claim 131 words
A method as in claim 1, wherein said criterion relates to at least one of: contrast in one of said layers and central position shift between said one of said layers and another of said layers; growth ratio between two of said layers compared to skewness in one of said two of said layers; growth ratio between two of said layers compared to standard deviation in one of said layers; shape factor in one of said layers compared to skewness in another of said layers; shape factor in one of said layers compared to shape factor in another of said layers; standard deviation in one of said layers compared to longest axis in another of said layers; and contrast in one of said layers compared to skewness another of said layers.
Claim 10
Independent Claim 84 words
A method of detecting abnormal regions in living tissue depicted in a digital radiograph, the method comprising: identifying suspected abnormal regions depicted in the radiograph; for each identified suspected abnormal region, (a) extracting multiple topographic layers of the region from the digital radiograph, the multiple topographic layers being extracted from the same radiograph; (b) determining features of the region in each of said layers; and (c) applying inter-layer multivariate criteria to said features to determine whether said suspected abnormal region is an abnormal region.
Claim 11
Independent Claim 84 words
A method of detecting abnormal regions in living tissue depicted in a digital radiograph, the method comprising: identifying suspected abnormal regions depicted in the radiograph; for each identified suspected abnormal region, (a) extracting multiple topographic layers of the region from the digital radiograph, the multiple topographic layers being extracted from the same radiograph; (b) determining features of the region in each of said layers; and (c) applying inter-layer multivariate criteria to said features to determine whether said suspected abnormal region is an abnormal region.
Claim 12
Independent Claim 98 words
An apparatus for detecting abnormal regions in living tissue depicted in a digital radiograph, the apparatus comprising: means for identifying suspected abnormal regions depicted in the radiograph; means for extracting multiple topographic layers of the region from the digital radiograph for each suspected abnormal region identified by the means for identifying, the multiple topographic layers all being extracted from the same radiograph; means for determining features in each of said layers extracted by the means for extracting; and means for applying inter-layer multivariate criteria to said features to determine whether said suspected abnormal region is an abnormal region.
Claim 13
Independent Claim 98 words
An apparatus for detecting abnormal regions in living tissue depicted in a digital radiograph, the apparatus comprising: means for identifying suspected abnormal regions depicted in the radiograph; means for extracting multiple topographic layers of the region from the digital radiograph for each suspected abnormal region identified by the means for identifying, the multiple topographic layers all being extracted from the same radiograph; means for determining features in each of said layers extracted by the means for extracting; and means for applying inter-layer multivariate criteria to said features to determine whether said suspected abnormal region is an abnormal region.
Claim 14
Dependent Claim 20 words
An apparatus as in claim 10, wherein said means for applying inter-layer multivariate criteria comprises means for applying non-linear criteria.
Claim 15
Dependent Claim 64 words
An apparatus as in claim 10, wherein said features of the region include at least one of: the size of the region, the shape of the region, the longest axis of the region; the contrast of the region; the standard deviation of the region; the skewness of the region; the size growth ratio of the region; and the central position shift of the region.
Claim 16
Dependent Claim 207 words
An apparatus as in claim 10, wherein said criteria relate to at least one of: (a) the contrast and the standard deviation in a third layer; (b) the shape factor and longest axis in the third layer; (c) the size and the contrast in a first layer; (d) the growth ratio between the first layer and a second layer compared to the growth ratio between the second and third layers; (e) the shape factor in the second layer and the central position shift between first and second layer; (f) the contrast in the first layer and central position shift between the first and second layer; (g) the growth ratio between the second and third layers compared to the skewness in the second layer; (h) the growth ratio between the second and third layers compared to standard deviation in the first layer; (i) the shape factor in the second layer compared to the skewness in the third layer; (j) the shape factor in the second layer compared to the shape factor in the third layer; (k) the standard deviation in the first layer compared to the longest axis in the second layer; and (l) the contrast in the first layer compared to the skewness in the second layer.
Claim 17
Dependent Claim 131 words
An apparatus as in claim 10, wherein said criteria relate to at least one of: contrast in one of said layers and central position shift between said one of said layers and another of said layers; growth ratio between two of said layers compared to skewness in one of said two of said layers; growth ratio between two of said layers compared to standard deviation in one of said layers; shape factor in one of said layers compared to skewness in another of said layers; shape factor in one of said layers compared to shape factor in another of said layers; standard deviation in one of said layers compared to longest axis in another of said layers; and contrast in one of said layers compared to skewness another of said layers.
Claim 18
Dependent Claim 23 words
A method as in claim 1 wherein the radiograph is a mammogram and wherein the abnormal region depicts a mass or clustered microcalcifications.
Claim 19
Dependent Claim 22 words
A method as in claim 9 wherein the radiograph is a mammogram and wherein the abnormal regions depict masses or clustered microcalcifications.
Claim 20
Dependent Claim 22 words
An apparatus as in claim 10 wherein the radiograph is a mammogram and wherein the abnormal regions depict masses or clustered microcalcifications.
Claim 21
Dependent Claim 25 words
A method as in claim 1 wherein the radiograph is produced from computed tomography of the liver and wherein the abnormal region depicts a mass.
Claim 22
Dependent Claim 24 words
A method as in claim 9 wherein the radiograph is produced from computed tomography of the liver and wherein the abnormal regions depict masses.
Claim 23
Dependent Claim 24 words
An apparatus as in claim 10 wherein the radiograph is produced from computed tomography of the liver and wherein the abnormal regions depict masses.
Claim 24
Dependent Claim 21 words
A method as in claim 1 wherein the radiograph is a chest x-ray and wherein the abnormal region depicts a nodule.
Claim 25
Dependent Claim 20 words
A method as in claim 9 wherein the radiograph is a chest x-ray and wherein the abnormal regions depict nodules.
Claim 26
Dependent Claim 20 words
An apparatus as in claim 10 wherein the radiograph is a chest x-ray and wherein the abnormal regions depict nodules.

References Cited (Backward Citations)

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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) 2001-11-16 2002-05-18 2002-11-17 $2000.00 Window Closed / Lapsed
7.5 Years (Year 8) 2005-11-16 2006-05-18 2006-11-17 $3760.00 Window Closed / Lapsed
11.5 Years (Year 12) 2009-11-16 2010-05-18 2010-11-17 $7700.00 Window Closed / Lapsed

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