WO2003087983A3 - Massive training artificial neural network (mtann) for detecting abnormalities in medical images - Google Patents

Massive training artificial neural network (mtann) for detecting abnormalities in medical images Download PDF

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Publication number
WO2003087983A3
WO2003087983A3 PCT/US2003/010468 US0310468W WO03087983A3 WO 2003087983 A3 WO2003087983 A3 WO 2003087983A3 US 0310468 W US0310468 W US 0310468W WO 03087983 A3 WO03087983 A3 WO 03087983A3
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WO
WIPO (PCT)
Prior art keywords
target structure
image
sub
training
pixel values
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PCT/US2003/010468
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French (fr)
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WO2003087983A2 (en
Inventor
Kenji Suzuki
Kunio Doi
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Univ Chicago
Kenji Suzuki
Kunio Doi
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Application filed by Univ Chicago, Kenji Suzuki, Kunio Doi filed Critical Univ Chicago
Priority to AU2003228448A priority Critical patent/AU2003228448A1/en
Publication of WO2003087983A2 publication Critical patent/WO2003087983A2/en
Publication of WO2003087983A3 publication Critical patent/WO2003087983A3/en

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    • 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

Abstract

A method of training an artificial neural network (ANN) involves receiving a likelihood distribution map as a teacher image, receiving a training image, moving a local window across sub-regions of the training image to obtain respective sub-region pixel sets, inputting the sub-region pixel sets to the ANN so that it provides output pixel values that are compared to output pixel values of corresponding teacher image pixel values to determine an error, and training the ANN to reduce the error. A method of detecting a target structure in an image involves scanning a local window across sub-regions of the image by moving the local window for each sub-region so as to obtain respective sub-region pixel sets, inputting the sub-region pixel sets to an ANN so that it provides respective output pixel values that represent likelihoods that respective image pixels are part of a target structure, the output pixel values collectively constituting a likelihood distribution map. Another method for detecting a target structure involves training N parallel ANNs on either (A) a same target structure and N mutually different non-target structures, or (B) a same non-target structure and N mutually different target structures, the ANNs outputting N respective indications of whether the image includes a target structure or a non-target structure, and combining the N indications to form a combined indication of whether the image includes a target structure or a non-target structure. The invention provides related apparatus and computer program products storing executable instructions to perform the methods.
PCT/US2003/010468 2002-04-12 2003-04-14 Massive training artificial neural network (mtann) for detecting abnormalities in medical images WO2003087983A2 (en)

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AU2003228448A AU2003228448A1 (en) 2002-04-12 2003-04-14 Massive training artificial neural network (mtann) for detecting abnormalities in medical images

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US10/120,420 US6819790B2 (en) 2002-04-12 2002-04-12 Massive training artificial neural network (MTANN) for detecting abnormalities in medical images
US10/120,420 2002-04-12

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WO2003087983A2 WO2003087983A2 (en) 2003-10-23
WO2003087983A3 true WO2003087983A3 (en) 2004-08-19

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Families Citing this family (128)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6721446B1 (en) * 1999-04-26 2004-04-13 Adobe Systems Incorporated Identifying intrinsic pixel colors in a region of uncertain pixels
US6941323B1 (en) 1999-08-09 2005-09-06 Almen Laboratories, Inc. System and method for image comparison and retrieval by enhancing, defining, and parameterizing objects in images
DE10044844A1 (en) * 2000-09-11 2002-04-04 Siemens Ag Method, device and software for separating the individual objects of an anatomical structure segmented from 3D data sets of medical examination methods
GB2397423B (en) * 2001-09-17 2005-06-01 Ca Minister Agriculture & Food A method and apparatus for identifying and quantifying characteristics of seeds and other small objects
CA2390056A1 (en) * 2002-06-07 2003-12-07 Du Pont Canada Inc. Method and system for managing commodity information in a supply chain of production
US7379574B2 (en) * 2002-11-27 2008-05-27 The Board Of Trustees Of The Leland Stanford Junior University Quantification of vascular irregularity
US7324675B2 (en) * 2002-11-27 2008-01-29 The Board Of Trustees Of The Leland Stanford Junior University Quantification of aortoiliac endoluminal irregularity
US20040116796A1 (en) * 2002-12-17 2004-06-17 Jianying Li Methods and apparatus for scoring a substance
US7613335B2 (en) * 2003-02-12 2009-11-03 The University Of Iowa Research Foundation Methods and devices useful for analyzing color medical images
JP3772845B2 (en) * 2003-03-24 2006-05-10 コニカミノルタホールディングス株式会社 Image processing program, image processing apparatus, and photographing apparatus
US7653225B2 (en) * 2003-09-17 2010-01-26 Siemens Corporation Method and system for ground glass nodule (GGN) segmentation with shape analysis
JP2008505704A (en) * 2004-07-09 2008-02-28 フィッシャー イメイジング コーポレイション Breast screening method in fusion mammography
US20060018524A1 (en) * 2004-07-15 2006-01-26 Uc Tech Computerized scheme for distinction between benign and malignant nodules in thoracic low-dose CT
US7392229B2 (en) * 2005-02-12 2008-06-24 Curtis L. Harris General purpose set theoretic processor
US7689016B2 (en) * 2005-05-27 2010-03-30 Stoecker & Associates, A Subsidiary Of The Dermatology Center, Llc Automatic detection of critical dermoscopy features for malignant melanoma diagnosis
US7577309B2 (en) * 2005-06-18 2009-08-18 Muralidhara Subbarao Direct vision sensor for 3D computer vision, digital imaging, and digital video
WO2007029467A1 (en) 2005-09-05 2007-03-15 Konica Minolta Medical & Graphic, Inc. Image processing method and image processing device
KR100682987B1 (en) * 2005-12-08 2007-02-15 한국전자통신연구원 Apparatus and method for three-dimensional motion recognition using linear discriminant analysis
CA2640683C (en) * 2006-01-31 2014-10-21 Canadian Space Agency Method and system for increasing signal-to-noise ratio
US20070211930A1 (en) * 2006-03-09 2007-09-13 Terry Dolwick Attribute based image enhancement and display for medical imaging applications
US7949162B2 (en) * 2006-08-14 2011-05-24 Siemens Medical Solutions Usa, Inc. System and method for solid component evaluation in mixed ground glass nodules
US7646936B2 (en) * 2006-10-03 2010-01-12 Varian Medical Systems International Ag Spatially variant image deformation
US8065249B1 (en) 2006-10-13 2011-11-22 Harris Curtis L GPSTP with enhanced aggregation functionality
US7774286B1 (en) 2006-10-24 2010-08-10 Harris Curtis L GPSTP with multiple thread functionality
US7940970B2 (en) 2006-10-25 2011-05-10 Rcadia Medical Imaging, Ltd Method and system for automatic quality control used in computerized analysis of CT angiography
US7860283B2 (en) 2006-10-25 2010-12-28 Rcadia Medical Imaging Ltd. Method and system for the presentation of blood vessel structures and identified pathologies
US7940977B2 (en) 2006-10-25 2011-05-10 Rcadia Medical Imaging Ltd. Method and system for automatic analysis of blood vessel structures to identify calcium or soft plaque pathologies
US7873194B2 (en) 2006-10-25 2011-01-18 Rcadia Medical Imaging Ltd. Method and system for automatic analysis of blood vessel structures and pathologies in support of a triple rule-out procedure
US7983459B2 (en) 2006-10-25 2011-07-19 Rcadia Medical Imaging Ltd. Creating a blood vessel tree from imaging data
US7792379B2 (en) * 2007-02-06 2010-09-07 Accenture Global Services Gmbh Transforming a submitted image of a person based on a condition of the person
US8529446B2 (en) * 2007-02-09 2013-09-10 Siemens Aktiengesellschaft Methods for determining parameters and planning clinical studies in automatic study and data management systems
US8107695B2 (en) * 2007-06-27 2012-01-31 General Electric Company Methods and systems for assessing patient movement in diagnostic imaging
US7899228B2 (en) * 2007-08-06 2011-03-01 Carestream Health, Inc. Line structure detection and analysis for mammography CAD
US20100104155A1 (en) * 2007-08-06 2010-04-29 Shoupu Chen Method for detection of linear structures and microcalcifications in mammographic images
US8203338B2 (en) * 2007-08-06 2012-06-19 Carestream Health, Inc. Linear structure verification in medical applications
US8224051B2 (en) * 2007-08-06 2012-07-17 Carestream Health, Inc. Method for detection of linear structures and microcalcifications in mammographic images
CN101373540B (en) * 2007-08-20 2011-12-14 鸿富锦精密工业（深圳）有限公司 System and method for simplifying point clouds
US10013638B2 (en) 2008-08-14 2018-07-03 Ping Zhang Cancer diagnostic method and system
US8290250B2 (en) * 2008-12-26 2012-10-16 Five Apes, Inc. Method and apparatus for creating a pattern recognizer
US8548231B2 (en) * 2009-04-02 2013-10-01 Siemens Corporation Predicate logic based image grammars for complex visual pattern recognition
DE102009038588A1 (en) * 2009-08-26 2011-03-24 Degudent Gmbh Method for determining a complete data record of an object to be measured
US8667230B1 (en) 2010-10-19 2014-03-04 Curtis L. Harris Recognition and recall memory
JP5911165B2 (en) * 2011-08-05 2016-04-27 株式会社メガチップス Image recognition device
JP5945803B2 (en) * 2012-03-07 2016-07-05 東芝メディカルシステムズ株式会社 Medical image interpretation system
US9060685B2 (en) * 2012-03-26 2015-06-23 Nec Laboratories America, Inc. Whole tissue classifier for histology biopsy slides
JP5993653B2 (en) * 2012-08-03 2016-09-14 キヤノン株式会社 Image processing apparatus, image processing method, and program
US9332953B2 (en) 2012-08-31 2016-05-10 The University Of Chicago Supervised machine learning technique for reduction of radiation dose in computed tomography imaging
US10209097B2 (en) * 2013-03-19 2019-02-19 Balluff Gmbh Inductive displacement measuring sensor and method for operating the latter
US9230192B2 (en) * 2013-11-15 2016-01-05 Adobe Systems Incorporated Image classification using images with separate grayscale and color channels
US9730660B2 (en) 2014-01-15 2017-08-15 Alara Systems, Inc. Converting low-dose to higher dose mammographic images through machine-learning processes
WO2015112932A1 (en) * 2014-01-25 2015-07-30 Handzel Amir Aharon Automated histological diagnosis of bacterial infection using image analysis
US10595805B2 (en) 2014-06-27 2020-03-24 Sunnybrook Research Institute Systems and methods for generating an imaging biomarker that indicates detectability of conspicuity of lesions in a mammographic image
EP3204871A1 (en) * 2014-10-09 2017-08-16 Microsoft Technology Licensing, LLC Generic object detection in images
US9563825B2 (en) 2014-11-20 2017-02-07 Adobe Systems Incorporated Convolutional neural network using a binarized convolution layer
US9418319B2 (en) 2014-11-21 2016-08-16 Adobe Systems Incorporated Object detection using cascaded convolutional neural networks
JP6435581B2 (en) * 2015-01-29 2018-12-12 パナソニックＩｐマネジメント株式会社 Transfer learning device, transfer learning system, transfer learning method and program
CN104700118A (en) * 2015-03-18 2015-06-10 中国科学院自动化研究所 Pulmonary nodule benignity and malignancy predicting method based on convolutional neural networks
US20160364527A1 (en) 2015-06-12 2016-12-15 Merge Healthcare Incorporated Methods and Systems for Automatically Analyzing Clinical Images and Determining when Additional Imaging May Aid a Diagnosis
CN105118044B (en) * 2015-06-16 2017-11-07 华南理工大学 A kind of wheel shape cast article defect automatic testing method
DE102015217429A1 (en) * 2015-09-11 2017-03-16 Siemens Healthcare Gmbh Diagnostic system and diagnostic procedure
CN105160361A (en) * 2015-09-30 2015-12-16 东软集团股份有限公司 Image identification method and apparatus
US9971953B2 (en) * 2015-12-10 2018-05-15 Intel Corporation Visual recognition using deep learning attributes
US10853449B1 (en) 2016-01-05 2020-12-01 Deepradiology, Inc. Report formatting for automated or assisted analysis of medical imaging data and medical diagnosis
EP3764281A1 (en) 2016-02-22 2021-01-13 Rapiscan Systems, Inc. Methods of identifying firearms in radiographic images
US10049307B2 (en) * 2016-04-04 2018-08-14 International Business Machines Corporation Visual object recognition
US10319094B1 (en) 2016-05-20 2019-06-11 Ccc Information Services Inc. Technology for capturing, transmitting, and analyzing images of objects
US10740891B1 (en) 2016-05-20 2020-08-11 Ccc Information Services Inc. Technology for analyzing images depicting vehicles according to base image models
US10636148B1 (en) 2016-05-20 2020-04-28 Ccc Information Services Inc. Image processing system to detect contours of an object in a target object image
US10657647B1 (en) 2016-05-20 2020-05-19 Ccc Information Services Image processing system to detect changes to target objects using base object models
US11288789B1 (en) 2016-05-20 2022-03-29 Ccc Intelligent Solutions Inc. Systems and methods for repairing a damaged vehicle using image processing
US9886771B1 (en) * 2016-05-20 2018-02-06 Ccc Information Services Inc. Heat map of vehicle damage
US10706321B1 (en) 2016-05-20 2020-07-07 Ccc Information Services Inc. Image processing system to align a target object in a target object image with an object model
US10043088B2 (en) * 2016-06-23 2018-08-07 Siemens Healthcare Gmbh Image quality score using a deep generative machine-learning model
DE102016113138B4 (en) * 2016-07-15 2018-02-15 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. System, in particular magnetic resonance system, for generating images
US10163040B2 (en) * 2016-07-21 2018-12-25 Toshiba Medical Systems Corporation Classification method and apparatus
CN113822960A (en) 2016-09-06 2021-12-21 医科达有限公司 Method, system and computer readable medium for generating synthetic imaging data
US10510146B2 (en) 2016-10-06 2019-12-17 Qualcomm Incorporated Neural network for image processing
US11449985B2 (en) * 2016-12-02 2022-09-20 Regents Of The University Of Minnesota Computer vision for cancerous tissue recognition
JP6813178B2 (en) * 2016-12-07 2021-01-13 学校法人常翔学園 Biological image processing device, output image manufacturing method, learning result manufacturing method, and program
EP3336800B1 (en) * 2016-12-19 2019-08-28 Siemens Healthcare GmbH Determination of a training function for generating annotated training images
US10140709B2 (en) * 2017-02-27 2018-11-27 International Business Machines Corporation Automatic detection and semantic description of lesions using a convolutional neural network
US11276163B2 (en) 2017-05-02 2022-03-15 Alvitae LLC System and method for facilitating autonomous control of an imaging system
JP7075416B2 (en) * 2017-05-18 2022-05-25 コーニンクレッカ フィリップス エヌ ヴェ Convolutional deep learning analysis of temporal heart images
US10140421B1 (en) 2017-05-25 2018-11-27 Enlitic, Inc. Medical scan annotator system
RU2667879C1 (en) * 2017-05-30 2018-09-24 Общество с ограниченной ответственностью "Аби Продакшн" Processing and analysis of data on computer-assisted tomography images
US10402995B2 (en) 2017-07-27 2019-09-03 Here Global B.V. Method, apparatus, and system for real-time object detection using a cursor recurrent neural network
US11517197B2 (en) * 2017-10-06 2022-12-06 Canon Medical Systems Corporation Apparatus and method for medical image reconstruction using deep learning for computed tomography (CT) image noise and artifacts reduction
US10803984B2 (en) 2017-10-06 2020-10-13 Canon Medical Systems Corporation Medical image processing apparatus and medical image processing system
US20190122104A1 (en) 2017-10-19 2019-04-25 General Electric Company Building a binary neural network architecture
US10460440B2 (en) 2017-10-24 2019-10-29 General Electric Company Deep convolutional neural network with self-transfer learning
US10346728B2 (en) 2017-10-26 2019-07-09 Hitachi, Ltd. Nodule detection with false positive reduction
EA201700561A1 (en) * 2017-11-16 2019-05-31 Общество С Ограниченной Ответственностью "Доммар" METHOD AND SYSTEM OF TEETH ALIGNMENT ON THE BASIS OF MODELING THE CROWN AND ROOTS MOVEMENT
US10832808B2 (en) 2017-12-13 2020-11-10 International Business Machines Corporation Automated selection, arrangement, and processing of key images
EP3625765B1 (en) 2017-12-29 2024-03-20 Leica Biosystems Imaging, Inc. Processing of histology images with a convolutional neural network to identify tumors
CN108281183A (en) * 2018-01-30 2018-07-13 重庆大学 Cervical smear image diagnostic system based on convolutional neural networks and transfer learning
CN108428229B (en) * 2018-03-14 2020-06-16 大连理工大学 Lung texture recognition method based on appearance and geometric features extracted by deep neural network
JP7093075B2 (en) 2018-04-09 2022-06-29 東芝エネルギーシステムズ株式会社 Medical image processing equipment, medical image processing methods, and programs
US11049606B2 (en) 2018-04-25 2021-06-29 Sota Precision Optics, Inc. Dental imaging system utilizing artificial intelligence
US10776923B2 (en) * 2018-06-21 2020-09-15 International Business Machines Corporation Segmenting irregular shapes in images using deep region growing
US10643092B2 (en) 2018-06-21 2020-05-05 International Business Machines Corporation Segmenting irregular shapes in images using deep region growing with an image pyramid
CN108742679B (en) * 2018-06-29 2022-07-05 上海联影医疗科技股份有限公司 Nodule detection apparatus and method
US10878570B2 (en) * 2018-07-17 2020-12-29 International Business Machines Corporation Knockout autoencoder for detecting anomalies in biomedical images
US10991092B2 (en) * 2018-08-13 2021-04-27 Siemens Healthcare Gmbh Magnetic resonance imaging quality classification based on deep machine-learning to account for less training data
CA3107776A1 (en) 2018-08-15 2020-02-20 Hyperfine Research, Inc. Deep learning techniques for suppressing artefacts in magnetic resonance images
CN109034140B (en) * 2018-09-13 2021-05-04 哈尔滨工业大学 Industrial control network signal abnormity detection method based on deep learning structure
KR20210064210A (en) * 2018-09-24 2021-06-02 홀로직, 인크. Breast Mapping and Abnormal Positioning
KR102653177B1 (en) * 2018-10-29 2024-04-01 삼성에스디에스 주식회사 Apparatus and method for extracting object information
US11282198B2 (en) 2018-11-21 2022-03-22 Enlitic, Inc. Heat map generating system and methods for use therewith
US11457871B2 (en) 2018-11-21 2022-10-04 Enlitic, Inc. Medical scan artifact detection system and methods for use therewith
US11145059B2 (en) 2018-11-21 2021-10-12 Enlitic, Inc. Medical scan viewing system with enhanced training and methods for use therewith
US10818386B2 (en) 2018-11-21 2020-10-27 Enlitic, Inc. Multi-label heat map generating system
US10726950B2 (en) * 2018-11-25 2020-07-28 Aivitae LLC Methods and systems for autonomous control of imaging devices
US20200202622A1 (en) * 2018-12-19 2020-06-25 Nvidia Corporation Mesh reconstruction using data-driven priors
CN110059813B (en) * 2019-02-13 2021-04-06 创新先进技术有限公司 Method, device and equipment for updating convolutional neural network by using GPU cluster
CA3133351A1 (en) * 2019-03-14 2020-09-17 Hyperfine, Inc. Deep learning techniques for generating magnetic resonance images from spatial frequency data
CN112102423A (en) * 2019-06-17 2020-12-18 通用电气精准医疗有限责任公司 Medical imaging method and system
WO2020252574A1 (en) 2019-06-17 2020-12-24 RecognAIse Technologies Inc. Artificial intelligence-based process and system for visual inspection of infrastructure
ES2955349T3 (en) 2019-09-18 2023-11-30 Bayer Ag MRI image prediction using a prediction model trained by supervised learning
WO2021053585A1 (en) 2019-09-18 2021-03-25 Bayer Aktiengesellschaft System, method, and computer program product for predicting, anticipating, and/or assessing tissue characteristics
CN110807788B (en) * 2019-10-21 2023-07-21 腾讯科技（深圳）有限公司 Medical image processing method, medical image processing device, electronic equipment and computer storage medium
US11462315B2 (en) 2019-11-26 2022-10-04 Enlitic, Inc. Medical scan co-registration and methods for use therewith
US11790492B1 (en) * 2019-12-18 2023-10-17 Thales Sa Method of and system for customized image denoising with model interpretations
SE1930421A1 (en) * 2019-12-30 2021-07-01 Unibap Ab Method and means for detection of imperfections in products
US11145060B1 (en) * 2020-07-20 2021-10-12 International Business Machines Corporation Automatic detection of vertebral dislocations
CN112396923B (en) * 2020-11-25 2023-09-19 贵州轻工职业技术学院 Marketing teaching simulation system
US20240038383A1 (en) * 2020-12-02 2024-02-01 Innsightful, Inc. Health Monitoring System
US11669678B2 (en) 2021-02-11 2023-06-06 Enlitic, Inc. System with report analysis and methods for use therewith
CN113033504B (en) * 2021-05-19 2021-08-27 广东众聚人工智能科技有限公司 Multi-scale video anomaly detection method

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6084981A (en) * 1994-11-29 2000-07-04 Hitachi Medical Corporation Image processing apparatus for performing image converting process by neural network

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5048100A (en) * 1988-12-15 1991-09-10 Michael Kuperstein Self organizing neural network method and system for general classification of patterns
JPH04364449A (en) * 1991-06-11 1992-12-16 Sumitomo Heavy Ind Ltd Fruit defect detecting apparatus
US5825936A (en) * 1994-09-22 1998-10-20 University Of South Florida Image analyzing device using adaptive criteria
US5642431A (en) * 1995-06-07 1997-06-24 Massachusetts Institute Of Technology Network-based system and method for detection of faces and the like
US5713364A (en) * 1995-08-01 1998-02-03 Medispectra, Inc. Spectral volume microprobe analysis of materials
US5873137A (en) * 1996-06-17 1999-02-23 Medogar Technologies Pnuematic mattress systems
JPH11261814A (en) * 1998-03-13 1999-09-24 Matsushita Electric Ind Co Ltd Discrimination system for image attribute

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6084981A (en) * 1994-11-29 2000-07-04 Hitachi Medical Corporation Image processing apparatus for performing image converting process by neural network

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SUZUKI ET AL.: "Neural filter with selection of input features and its application to image quality improvement of medical image sequences", IEEE, November 2000 (2000-11-01), pages 783 - 788, XP002973223 *

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US20030194124A1 (en) 2003-10-16
AU2003228448A8 (en) 2003-10-27
WO2003087983A2 (en) 2003-10-23
US6819790B2 (en) 2004-11-16
AU2003228448A1 (en) 2003-10-27

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