WO2004044845A3 - Image analysis - Google Patents

Image analysis Download PDF

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Publication number
WO2004044845A3
WO2004044845A3 PCT/GB2003/004841 GB0304841W WO2004044845A3 WO 2004044845 A3 WO2004044845 A3 WO 2004044845A3 GB 0304841 W GB0304841 W GB 0304841W WO 2004044845 A3 WO2004044845 A3 WO 2004044845A3
Authority
WO
WIPO (PCT)
Prior art keywords
pixels
image
duct
analysis
epithelial cells
Prior art date
Application number
PCT/GB2003/004841
Other languages
French (fr)
Other versions
WO2004044845A2 (en
Inventor
John Francis Haddon
Sharon Katrina Watson
Original Assignee
Qinetiq Ltd
John Francis Haddon
Sharon Katrina Watson
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Qinetiq Ltd, John Francis Haddon, Sharon Katrina Watson filed Critical Qinetiq Ltd
Priority to JP2004550796A priority Critical patent/JP2006505782A/en
Priority to US10/533,204 priority patent/US7555161B2/en
Priority to AU2003280023A priority patent/AU2003280023A1/en
Priority to DE60329522T priority patent/DE60329522D1/en
Priority to EP03772425A priority patent/EP1563457B1/en
Priority to AT03772425T priority patent/ATE444541T1/en
Publication of WO2004044845A2 publication Critical patent/WO2004044845A2/en
Publication of WO2004044845A3 publication Critical patent/WO2004044845A3/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/695—Preprocessing, e.g. image segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G06T7/41—Analysis of texture based on statistical description of texture
    • G06T7/45—Analysis of texture based on statistical description of texture using co-occurrence matrix computation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/698—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10056—Microscopic image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30068—Mammography; Breast
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30096—Tumor; Lesion

Abstract

A method for the automated analysis of digital images, particularly for the purpose of assessing the presence and severity of cancer in breast tissue based on the relative proportions of tubule formations and epithelial cells identified in digital images of histological slides. The method includes the step of generating a property co-occurrence matrix (PCM) from some or all of the pixels in the image, using the properties of local mean and local standard deviation of intensity in neighbourhoods of the selected pixels, and segmenting the image by labelling the selected pixels as belonging to specified classes based upon analysis of the PCM. In this way relatively dark and substantially textured regions representing epithelial cells in the image can be distinguished from lighter and more uniform background regions. Other steps include identifying groups of pixels representing duct cells in the image based on intensity, shape and size criteria, dilating those pixels into surrounding groups labelled as epithelial cells by a dimension to correspond to an overall tubule formation, and calculating a metric based on the ratio of the number of duct pixels after such dilation to the total number of duct and epithelial pixels. Other uses for the method could include the analysis of mineral samples containing certain types of crystal formations.
PCT/GB2003/004841 2002-11-12 2003-11-10 Image analysis WO2004044845A2 (en)

Priority Applications (6)

Application Number Priority Date Filing Date Title
JP2004550796A JP2006505782A (en) 2002-11-12 2003-11-10 Image analysis
US10/533,204 US7555161B2 (en) 2002-11-12 2003-11-10 Image analysis
AU2003280023A AU2003280023A1 (en) 2002-11-12 2003-11-10 Image analysis
DE60329522T DE60329522D1 (en) 2002-11-12 2003-11-10 IMAGE ANALYSIS
EP03772425A EP1563457B1 (en) 2002-11-12 2003-11-10 Image analysis
AT03772425T ATE444541T1 (en) 2002-11-12 2003-11-10 IMAGE ANALYSIS

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB0226331A GB2395263A (en) 2002-11-12 2002-11-12 Image analysis
GB0226331.7 2002-11-12

Publications (2)

Publication Number Publication Date
WO2004044845A2 WO2004044845A2 (en) 2004-05-27
WO2004044845A3 true WO2004044845A3 (en) 2004-08-26

Family

ID=9947646

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/GB2003/004841 WO2004044845A2 (en) 2002-11-12 2003-11-10 Image analysis

Country Status (9)

Country Link
US (1) US7555161B2 (en)
EP (1) EP1563457B1 (en)
JP (1) JP2006505782A (en)
CN (1) CN100401321C (en)
AT (1) ATE444541T1 (en)
AU (1) AU2003280023A1 (en)
DE (1) DE60329522D1 (en)
GB (1) GB2395263A (en)
WO (1) WO2004044845A2 (en)

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Also Published As

Publication number Publication date
AU2003280023A1 (en) 2004-06-03
JP2006505782A (en) 2006-02-16
US7555161B2 (en) 2009-06-30
ATE444541T1 (en) 2009-10-15
GB2395263A (en) 2004-05-19
DE60329522D1 (en) 2009-11-12
WO2004044845A2 (en) 2004-05-27
CN100401321C (en) 2008-07-09
EP1563457A2 (en) 2005-08-17
CN1735907A (en) 2006-02-15
GB0226331D0 (en) 2002-12-18
US20060002608A1 (en) 2006-01-05
EP1563457B1 (en) 2009-09-30

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