US6738500B2
Expired / Lapsed
US
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Method and system for detecting small structures in images
Assignee: Johns Hopkins University
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Filing: 2002-08-26
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Granted: 2004-05-18
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Expires: 2022-08-26
Abstract
Abstract The invention is a method and apparatus for automated detection of small structures in images. One specific use is to detect malignant microcalcification clusters in mammograms. A digitized and filtered mammogram image is stored in a computer. Seed pixels, which are pixels that are brighter than their immediate neighbors, are identified to indicate candidate structures and used to construct two regions. Various features are then measured using the two regions around each seed point. The features characterize each candidate structure and are input to a classifier, such as a neural network. The classifier then distinguishes between structures of interest and background. The structures detected by the classifier are then presented to a clustering algorithm. A detected structure that is less than a threshold distance away from the nearest structure and a cluster is included in that cluster. Finally, the results are displayed, either on a monitor or on hard copy, with a frame around the detected cluster.
Inventors
- 👤 Isaac N. Bankman
- 👤 Lloyd W. Ison
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 22:26
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/0002; G06T7/0012; G06T7/10; G06T7/11; G06T7/187; G06V; G06V10/00; G06V10/20; G06V10/26; G06V10/267; G06T2207/00; G06T2207/10; G06T2207/10116; G06T2207/20; G06T2207/20092; G06T2207/20101; G06T2207/20112; G06T2207/20156; G06T2207/30; G06T2207/30004; G06T2207/30068; G06T2207/30096; G06V2201/00; G06V2201/03; G06V2201/032
Claims Analysis
Total Claims: 26
Claim 1
Independent Claim
217 words
A method for detecting a structure in an image, the method comprising the steps of: digitizing the image; storing the digitized image in a memory of a data processing means; detecting automatically the structure using the data processing means and the digitized image comprising the steps of: segmenting the digitized image into a candidate structure to be classified comprising the steps of: locating a seed pixel in the digitized image, the seed pixel having a higher intensity value than its neighboring pixels; forming a gradient image of the digitized image; constructing a first region beginning with the seed pixel and its neighboring pixels by adding to the first region all adjacent pixels having both a gradient value higher and a gray level lower than the pixels already in the first region that the adjacent pixels adjoin; and constructing a second region beginning with the seed pixel and its neighboring pixels by adding to the second region all adjacent pixels having a gray level value lower than the pixels already in the second region that the adjacent pixels adjoin; and extracting features from the candidate structure; characterizing the candidate structure using the features; and classifying the candidate structure, using the extracted features, as structure or as back ground; and indicating the location of the structure in the image.
Claim 2
Independent Claim
217 words
A method for detecting a structure in an image, the method comprising the steps of: digitizing the image; storing the digitized image in a memory of a data processing means; detecting automatically the structure using the data processing means and the digitized image comprising the steps of: segmenting the digitized image into a candidate structure to be classified comprising the steps of: locating a seed pixel in the digitized image, the seed pixel having a higher intensity value than its neighboring pixels; forming a gradient image of the digitized image; constructing a first region beginning with the seed pixel and its neighboring pixels by adding to the first region all adjacent pixels having both a gradient value higher and a gray level lower than the pixels already in the first region that the adjacent pixels adjoin; and constructing a second region beginning with the seed pixel and its neighboring pixels by adding to the second region all adjacent pixels having a gray level value lower than the pixels already in the second region that the adjacent pixels adjoin; and extracting features from the candidate structure; characterizing the candidate structure using the features; and classifying the candidate structure, using the extracted features, as structure or as back ground; and indicating the location of the structure in the image.
Claim 3
Dependent Claim
18 words
The method as recited in claim 1 , wherein the candidate structure is classified using a neural network.
Claim 4
Dependent Claim
17 words
The method as recited in claim 2 , wherein the neural network is a feedforward neural network.
Claim 5
Dependent Claim
29 words
The method as recited in claim 1 , further comprising the step of clustering the classified structures that are a threshold distance from each other in the digitized image.
Claim 6
Dependent Claim
31 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring the standard deviation of pixel values along the edge of the second region (estd).
Claim 7
Dependent Claim
26 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring a gray level value of the seed pixel (sv).
Claim 8
Dependent Claim
27 words
The method as recited in claim 5 , the extracting features step further comprising the step of measuring a gray level value of the seed pixel (sv).
Claim 9
Dependent Claim
28 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring an area of the first region in pixels (a 1 ).
Claim 10
Dependent Claim
29 words
The method as recited in claim 7 , the extracting features step further comprising the step of measuring an area of the first region in pixels (a 1 ).
Claim 11
Dependent Claim
28 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring an area of the second region in pixels (a 2 ).
Claim 12
Dependent Claim
29 words
The method as recited in claim 9 , the extracting features step further comprising the step of measuring an area of the second region in pixels (a 2 ).
Claim 13
Dependent Claim
43 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring a local contrast obtained by subtracting the mean value of pixels along the edge of the first region from the seed pixel value (ac 1 ).
Claim 14
Dependent Claim
42 words
The method as recited in claim 11 , the extracting features step further comprising the step of measuring a local contrast obtained by subtracting the mean value of pixels along the edge of the first region from the seed pixel value (acl).
Claim 15
Dependent Claim
43 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring a local contrast obtained by subtracting the mean value of pixels along the edge of the second region from the seed pixel value (ac 2 ).
Claim 16
Dependent Claim
44 words
The method as recited in claim 13 , the extracting features step further comprising the step of measuring a local contrast obtained by subtracting the mean value of pixels along the edge of the second region from the seed pixel value (ac 2 ).
Claim 17
Dependent Claim
42 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring the mean value of the higher fifty percentile of the gradient values of the pixels along the edge of the first region (mxs 1 ).
Claim 18
Dependent Claim
43 words
The method as recited in claim 15 , the extracting features step further comprising the step of measuring the mean value of the higher fifty percentile of the gradient values of the pixels along the edge of the first region (mxs 1 ).
Claim 19
Dependent Claim
48 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring the mean value of the higher fifty percentile of the gray level differences between the seed pixel value and each pixel along the edge of the second region (mxc 2 ).
Claim 20
Dependent Claim
49 words
The method as recited in claim 17 , the extracting features step further comprising the step of measuring the mean value of the higher fifty percentile of the gray level differences between the seed pixel value and each pixel along the edge of the second region (mxc 2 ).
Claim 21
Dependent Claim
25 words
The method as recited in claim 1 , the extracting features step comprising the step of measuring the mean angle index of the structure (aa).
Claim 22
Dependent Claim
26 words
The method as recited in claim 19 , the extracting features step further comprising the step of measuring the mean angle index of the structure (aa).
Claim 23
Dependent Claim
36 words
The method as recited in claim 21 , the extracting features step further comprising the step of dividing the area of the first region by the area of the second region (a 1 /a 2 ).
Claim 24
Dependent Claim
38 words
The method as recited in claim 22 , the extracting features step further comprising the step of dividing the local contrast of the first region by the local contrast of the second region (ac 1 /ac 2 ).
Claim 25
Independent Claim
45 words
The method as recited in claims 23 , the characterizing the candidate structure comprising the step of selecting the sv, a 2 , a 1 /a 2 , acl, acl/ac 2 , rnxsl, mxc 2 , estd, and aa features to characterize the candidate structure.
Claim 26
Dependent Claim
20 words
The method as recited in claim 24 , wherein the image is a mammogram and the structure is a microcalcification.
References Cited (Backward Citations)
US5212637A
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2007-05-18 | 2007-11-17 | 2008-05-18 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2011-05-18 | 2011-11-17 | 2012-05-18 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2015-05-18 | 2015-11-17 | 2016-05-18 | $7700.00 | Window Closed / Lapsed |