WO2006034223A3 - System and method for hyper-spectral analysis - Google Patents

System and method for hyper-spectral analysis Download PDF

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Publication number
WO2006034223A3
WO2006034223A3 PCT/US2005/033527 US2005033527W WO2006034223A3 WO 2006034223 A3 WO2006034223 A3 WO 2006034223A3 US 2005033527 W US2005033527 W US 2005033527W WO 2006034223 A3 WO2006034223 A3 WO 2006034223A3
Authority
WO
WIPO (PCT)
Prior art keywords
classifiers
compute
spectra
patch
classifier
Prior art date
Application number
PCT/US2005/033527
Other languages
French (fr)
Other versions
WO2006034223A2 (en
Inventor
Mauro M Maggioni
Ronald R Coifman
Andreas C Coppi
Gustave L Davis
Richard A Deverse
William G Fateley
Frank Geshwind
Frederick J Warner
Original Assignee
Plain Sight Systems Inc
Mauro M Maggioni
Ronald R Coifman
Andreas C Coppi
Gustave L Davis
Richard A Deverse
William G Fateley
Frank Geshwind
Frederick J Warner
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
Priority claimed from US11/075,257 external-priority patent/US7219086B2/en
Application filed by Plain Sight Systems Inc, Mauro M Maggioni, Ronald R Coifman, Andreas C Coppi, Gustave L Davis, Richard A Deverse, William G Fateley, Frank Geshwind, Frederick J Warner filed Critical Plain Sight Systems Inc
Publication of WO2006034223A2 publication Critical patent/WO2006034223A2/en
Publication of WO2006034223A3 publication Critical patent/WO2006034223A3/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
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12—Classification; Matching
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Data Mining & Analysis (AREA)
  • Molecular Biology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Biomedical Technology (AREA)
  • Multimedia (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

An improved method and system for classifying tissue samples comprises determining a tissue type classification based on spectral data of training samples of known target classification. Pixels are extrated around elements to be characterized in figure 11. (Step 2000). Statistics of the spectra are computed (Step 2010). Compute a first classifier from frequency- wise standard deviation of the spectra in each patch (Step 2020). Compute a second set of classifiers from principal components of the spectra in each patch (Step 2030). Compute a classifier based on the output of the first two classifiers/sets of classifiers (Step 2040). Characterize elements within the input image based on the results fo the classifiers (Step 2050).
PCT/US2005/033527 2004-09-17 2005-09-19 System and method for hyper-spectral analysis WO2006034223A2 (en)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US61093104P 2004-09-17 2004-09-17
US60/610,931 2004-09-17
US11/075,257 2005-03-07
US11/075,257 US7219086B2 (en) 1999-04-09 2005-03-07 System and method for hyper-spectral analysis

Publications (2)

Publication Number Publication Date
WO2006034223A2 WO2006034223A2 (en) 2006-03-30
WO2006034223A3 true WO2006034223A3 (en) 2009-04-09

Family

ID=36090594

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2005/033527 WO2006034223A2 (en) 2004-09-17 2005-09-19 System and method for hyper-spectral analysis

Country Status (1)

Country Link
WO (1) WO2006034223A2 (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2102031A1 (en) 2006-12-08 2009-09-23 Johnson Controls Technology Company Vehicle seat with lumbar support
CN106198000A (en) * 2016-07-11 2016-12-07 太原理工大学 A kind of rocker arm of coal mining machine gear failure diagnosing method
CN111528793B (en) * 2020-05-12 2022-06-21 宁波蓝明信息科技有限公司 Retinal blood vessel optical radiography imaging system and method
CN113762389B (en) * 2021-09-08 2024-04-12 大连海事大学 Hyperspectral image small sample classification method based on dynamic diagnosis

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5596992A (en) * 1993-06-30 1997-01-28 Sandia Corporation Multivariate classification of infrared spectra of cell and tissue samples
US20020146160A1 (en) * 2001-01-19 2002-10-10 Parker Mary F. Method and apparatus for generating two-dimensional images of cervical tissue from three-dimensional hyperspectral cubes

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5596992A (en) * 1993-06-30 1997-01-28 Sandia Corporation Multivariate classification of infrared spectra of cell and tissue samples
US20020146160A1 (en) * 2001-01-19 2002-10-10 Parker Mary F. Method and apparatus for generating two-dimensional images of cervical tissue from three-dimensional hyperspectral cubes

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SAITO N.ET AL: "Local Discriminant Bases and Their Applications", December 1995, pages: 337 - 358, XP008040592 *

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