AU2020401794A1 - Method for determining severity of skin disease based on percentage of body surface area covered by lesions - Google Patents

Method for determining severity of skin disease based on percentage of body surface area covered by lesions Download PDF

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Publication number
AU2020401794A1
AU2020401794A1 AU2020401794A AU2020401794A AU2020401794A1 AU 2020401794 A1 AU2020401794 A1 AU 2020401794A1 AU 2020401794 A AU2020401794 A AU 2020401794A AU 2020401794 A AU2020401794 A AU 2020401794A AU 2020401794 A1 AU2020401794 A1 AU 2020401794A1
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regions
image
training set
segmentation
lesion
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AU2020401794A
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Yanqing Chen
Ernesto J. MUNOZ-ELIAS
Charles Tang
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Janssen Biotech Inc
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Janssen Biotech Inc
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Publication of AU2020401794A1 publication Critical patent/AU2020401794A1/en
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    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/11Region-based segmentation
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformations in the plane of the image
    • G06T3/40Scaling of whole images or parts thereof, e.g. expanding or contracting
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • G06T7/0014Biomedical image inspection using an image reference approach
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20081Training; Learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20084Artificial neural networks [ANN]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30088Skin; Dermal
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30096Tumor; Lesion

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Artificial Intelligence (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Image Analysis (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
AU2020401794A 2019-12-09 2020-12-08 Method for determining severity of skin disease based on percentage of body surface area covered by lesions Pending AU2020401794A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201962945642P 2019-12-09 2019-12-09
US62/945,642 2019-12-09
PCT/IB2020/061648 WO2021116909A1 (en) 2019-12-09 2020-12-08 Method for determining severity of skin disease based on percentage of body surface area covered by lesions

Publications (1)

Publication Number Publication Date
AU2020401794A1 true AU2020401794A1 (en) 2022-07-28

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AU2020401794A Pending AU2020401794A1 (en) 2019-12-09 2020-12-08 Method for determining severity of skin disease based on percentage of body surface area covered by lesions

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US (2) US11538167B2 (https=)
EP (1) EP4073752A4 (https=)
JP (1) JP7695243B2 (https=)
KR (1) KR20220108158A (https=)
CN (1) CN114830173A (https=)
AU (1) AU2020401794A1 (https=)
BR (1) BR112022011111A2 (https=)
CA (1) CA3164066A1 (https=)
IL (1) IL293654A (https=)
WO (1) WO2021116909A1 (https=)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11538167B2 (en) * 2019-12-09 2022-12-27 Janssen Biotech, Inc. Method for determining severity of skin disease based on percentage of body surface area covered by lesions
US11659998B2 (en) 2020-03-05 2023-05-30 International Business Machines Corporation Automatic measurement using structured lights
US11484245B2 (en) * 2020-03-05 2022-11-01 International Business Machines Corporation Automatic association between physical and visual skin properties
CN119206306A (zh) * 2022-03-02 2024-12-27 深圳硅基智能科技有限公司 识别医学图像中的目标的方法及电子设备
CN114882018B (zh) * 2022-06-30 2022-10-25 杭州咏柳科技有限公司 一种基于图像的银屑病严重程度的评估系统
CN115830377B (zh) * 2022-11-28 2026-01-06 青岛大学 基于有限数据的深度学习用于皮肤癌图像分类的方法
US12119118B2 (en) * 2022-12-09 2024-10-15 BelleTorus Corporation Compute system with hidradenitis suppurativa severity diagnostic mechanism and method of operation thereof
WO2025078613A1 (fr) * 2023-10-11 2025-04-17 Term Helvet Sa Procédé de traitement de données relatives à des images

Family Cites Families (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7454046B2 (en) * 2005-09-20 2008-11-18 Brightex Bio-Photonics, Llc Method and system for analyzing skin conditions using digital images
US8005294B2 (en) 2006-11-29 2011-08-23 The Mitre Corporation Cursive character handwriting recognition system and method
MY145600A (en) * 2010-03-29 2012-03-01 Inst Of Technology Petronas Sdn Bhd A methodology and apparatus for objective assessment and rating of psoriasis lesion thickness using digital imaging
MY150801A (en) 2010-11-08 2014-02-28 Inst Of Technology Petronas Sdn Bhd A methodology and apparatus for objective, non-invasive and in vivo assessment and rating of psoriasis lesion scaliness using digital imaging
US8705860B2 (en) * 2011-03-14 2014-04-22 Microsoft Corporation Grouping variables for fast image labeling
US8879855B2 (en) * 2012-08-17 2014-11-04 Nec Laboratories America, Inc. Image segmentation for large-scale fine-grained recognition
US9307926B2 (en) * 2012-10-05 2016-04-12 Volcano Corporation Automatic stent detection
WO2014109708A1 (en) * 2013-01-08 2014-07-17 Agency For Science, Technology And Research A method and system for assessing fibrosis in a tissue
US20140316235A1 (en) 2013-04-18 2014-10-23 Digimarc Corporation Skin imaging and applications
CN104346801B (zh) * 2013-08-02 2018-07-20 佳能株式会社 图像构图评估装置、信息处理装置及其方法
US10032287B2 (en) 2013-10-30 2018-07-24 Worcester Polytechnic Institute System and method for assessing wound
US9286537B2 (en) * 2014-01-22 2016-03-15 Cognizant Technology Solutions India Pvt. Ltd. System and method for classifying a skin infection
SG10201405182WA (en) * 2014-08-25 2016-03-30 Univ Singapore Technology & Design Method and system
EP3367887A4 (en) 2015-10-28 2019-05-22 Spectral MD Inc. METHOD AND DEVICES FOR THE MULTISPEKTRAL, TIME RESOLVED OPTICAL IMAGING FOR TISSUE CLASSIFICATION
US9830710B2 (en) 2015-12-16 2017-11-28 General Electric Company Systems and methods for hair segmentation
US9886758B2 (en) * 2016-03-31 2018-02-06 International Business Machines Corporation Annotation of skin image using learned feature representation
WO2018107371A1 (zh) * 2016-12-13 2018-06-21 上海联影医疗科技有限公司 图像搜索系统及方法
US10366490B2 (en) 2017-03-27 2019-07-30 Siemens Healthcare Gmbh Highly integrated annotation and segmentation system for medical imaging
CN108230294B (zh) * 2017-06-14 2020-09-29 北京市商汤科技开发有限公司 图像检测方法、装置、电子设备和存储介质
US20190108912A1 (en) * 2017-10-05 2019-04-11 Iquity, Inc. Methods for predicting or detecting disease
US11010902B2 (en) * 2018-06-04 2021-05-18 University Of Central Florida Research Foundation, Inc. Capsules for image analysis
CN109363640A (zh) * 2018-12-04 2019-02-22 北京贝叶科技有限公司 基于皮肤病理图像的识别方法及系统
WO2020146489A1 (en) * 2019-01-08 2020-07-16 The Rockefeller University Hyperspectral imaging in automated digital dermoscopy screening for melanoma
EP3963541A1 (en) * 2019-04-29 2022-03-09 UCB Biopharma SRL Medical image analysis system and method for identification of lesions
US11341635B2 (en) * 2019-10-31 2022-05-24 Tencent America LLC Computer aided diagnosis system for detecting tissue lesion on microscopy images based on multi-resolution feature fusion
US11538167B2 (en) * 2019-12-09 2022-12-27 Janssen Biotech, Inc. Method for determining severity of skin disease based on percentage of body surface area covered by lesions

Also Published As

Publication number Publication date
US11915428B2 (en) 2024-02-27
EP4073752A1 (en) 2022-10-19
US20230060162A1 (en) 2023-03-02
JP2023504901A (ja) 2023-02-07
CN114830173A (zh) 2022-07-29
BR112022011111A2 (pt) 2022-08-23
US11538167B2 (en) 2022-12-27
EP4073752A4 (en) 2024-01-03
JP7695243B2 (ja) 2025-06-18
KR20220108158A (ko) 2022-08-02
CA3164066A1 (en) 2021-06-17
WO2021116909A1 (en) 2021-06-17
US20210174512A1 (en) 2021-06-10
IL293654A (en) 2022-08-01

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