JP7124041B2 - ハンナ病変の指摘のためのプログラム - Google Patents
ハンナ病変の指摘のためのプログラム Download PDFInfo
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- 230000003902 lesion Effects 0.000 title claims description 62
- 238000000034 method Methods 0.000 claims description 11
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- 208000005615 Interstitial Cystitis Diseases 0.000 description 21
- 238000001514 detection method Methods 0.000 description 16
- 238000013527 convolutional neural network Methods 0.000 description 13
- 230000011218 segmentation Effects 0.000 description 13
- 238000003745 diagnosis Methods 0.000 description 8
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- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 238000002474 experimental method Methods 0.000 description 3
- 210000004877 mucosa Anatomy 0.000 description 3
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- 208000025865 Ulcer Diseases 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 2
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- 230000005824 bladder abnormality Effects 0.000 description 2
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- 238000003384 imaging method Methods 0.000 description 2
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- 206010005063 Bladder pain Diseases 0.000 description 1
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- 206010011796 Cystitis interstitial Diseases 0.000 description 1
- 206010020853 Hypertonic bladder Diseases 0.000 description 1
- 206010029113 Neovascularisation Diseases 0.000 description 1
- 208000009722 Overactive Urinary Bladder Diseases 0.000 description 1
- 206010035664 Pneumonia Diseases 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
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- 238000011161 development Methods 0.000 description 1
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- 208000020629 overactive bladder Diseases 0.000 description 1
- 238000011160 research Methods 0.000 description 1
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- 208000024891 symptom Diseases 0.000 description 1
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Classifications
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- 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
- G06T7/0014—Biomedical image inspection using an image reference approach
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
- A61B1/00002—Operational features of endoscopes
- A61B1/00004—Operational features of endoscopes characterised by electronic signal processing
-
- 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
-
- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
- A61B1/00002—Operational features of endoscopes
- A61B1/00004—Operational features of endoscopes characterised by electronic signal processing
- A61B1/00009—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope
- A61B1/000094—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope extracting biological structures
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
- A61B1/00002—Operational features of endoscopes
- A61B1/00004—Operational features of endoscopes characterised by electronic signal processing
- A61B1/00009—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope
- A61B1/000096—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope using artificial intelligence
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
- A61B1/307—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor for the urinary organs, e.g. urethroscopes, cystoscopes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G—PHYSICS
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- G06N3/00—Computing arrangements based on biological models
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- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
- A61B1/06—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor with illuminating arrangements
- A61B1/0638—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor with illuminating arrangements providing two or more wavelengths
-
- 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
- G06T2207/10068—Endoscopic image
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- G—PHYSICS
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- 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
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- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
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- General Physics & Mathematics (AREA)
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- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Signal Processing (AREA)
- Databases & Information Systems (AREA)
- Urology & Nephrology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Computational Linguistics (AREA)
- Image Analysis (AREA)
- Endoscopes (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Description
膀胱内視鏡で撮影した動画を基に、この動画に対する正解情報の付与(アノテーション)を以下の手順で行われた。
1.全フレームから10フレーム毎に候補画像を抽出し、ハンナ病変候補画像を選定
2.選定画像に正解情報を付与
3.正解情報を付与した画像の前後のフレームで類似する画像に対し正解情報を付与
検出モデルとセグメンテーションモデルを使用して実験を行った。検出モデルとは、ハンナ病変領域を包含する矩形領域を推定するモデルであり、矩形領域の位置、大きさ、当該矩形の病変確信度を出力する。セグメンテーションモデルとは、画素毎の病変確信度を出力するモデルであり、ハンナ病変領域が形状も含め推定される。
検出モデル:Cascade R-CNN
セグメンテーションモデル:Cascade Mask R-CNN
セグメンテーションモデル:OCNet
上記3つのモデルをNBI、WLIそれぞれのデータで学習し、計6個のモデルを作成した。
実験では、データセットを85%の学習データと15%のテストデータにランダムに5回分割し、5回学習・評価を行った。なお、データ分割は症例単位で行っている。表3、表4に、NBI、WLIデータセットそれぞれの画像数および症例数を示す。
Sensitivity = #TP / (#TP + #FN)
PPV = #TP / (#TP+#FP)
である。
TP ≡ 1画素以上重なる全予測領域とのIoUが0.3を超える正解領域
FN ≡ 1画素以上重なる全予測領域とのIoUが0.3以下の正解領域
FP ≡ 正解領域とのIoUが0.1以下の予測領域
表 5:NBI画像で評価した検出モデル(Cascade R-CNN)の性能
表 6:NBI画像で評価したセグメンテーションモデルの性能
表 7:WLI画像で評価した検出モデル(Cascade R-CNN)の性能
表 8:WLI画像で評価したセグメンテーションモデルの性能
矩形出力は確信度と共に表示されている。
本例では泡を泡として出力表示する態様としている。
Claims (12)
- 膀胱中のハンナ病変の内視鏡画像データを取得し、
膀胱内視鏡画像を入力、内視鏡画像中におけるハンナ病変の位置指摘データを出力とする学習モデルに、対象の膀胱内視鏡画像を入力して、ハンナ病変の位置指摘を出力する処理をコンピュータに実行させるプログラム。 - 教師データとしての膀胱中のハンナ病変の内視鏡画像データが、狭帯域光観察画像と白色光観察画像のいずれをも含む、請求項1に記載のプログラム。
- 前記学習モデルが、ハンナ病変が存在しないが、正常膀胱の内視鏡画像データと、
正常膀胱ではないがハンナ病変が存在しない内視鏡画像データと、
を教師データとしてさらに含む、請求項1又は2に記載のプログラム。 - 膀胱内に存在する空気の内視鏡画像データを教師データとしてさらに含む、請求項1から3のいずれか1項に記載のプログラム。
- 正常膀胱であるか否かを判断して出力する処理をさらに含む、請求項3又は4に記載のプログラム。
- 膀胱内視鏡システムを用いて取得された膀胱内視鏡画像を用いた学習済みモデルであって、
膀胱内視鏡画像が入力される入力層と、
内視鏡画像中におけるハンナ病変の位置指摘データを出力とする出力層と、
膀胱中のハンナ病変の内視鏡画像データを入力、
膀胱画像中におけるハンナ病変の位置指摘データを出力とする教師データを用いてパラメータが学習された中間層とを備え、
対象の膀胱内視鏡画像を前記入力層に入力し、前記中間層にて演算し、画像中におけるハンナ病変の位置指摘データを出力するよう、
コンピュータを機能させるための学習済みモデル。 - 膀胱内に存在する空気の内視鏡画像データを教師データとしてさらに含む、請求項6に記載の学習済みモデル。
- 正常膀胱の内視鏡画像データと、
ハンナ病変が存在しないが、正常膀胱ではない内視鏡画像データとを教師データとしてさらに含む、請求項6又は7に記載の学習済みモデル。 - 前記教師データにおける前記内視鏡画像データが、狭帯域光観察画像と白色光観察画像のいずれをも含む、請求項6から8のいずれか1項に記載の学習済みモデル。
- 正常膀胱か異常膀胱かを出力としてさらに含む、請求項8又は9に記載の学習済みモデル。
- 請求項1から5のいずれか1項に記載のプログラムが記録された、膀胱内視鏡の制御装置。
- 請求項6から10のいずれか1項に記載の学習済みモデルが記録された、膀胱内視鏡の制御装置。
Priority Applications (8)
Application Number | Priority Date | Filing Date | Title |
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JP2020195447A JP7124041B2 (ja) | 2020-11-25 | 2020-11-25 | ハンナ病変の指摘のためのプログラム |
TW110140382A TW202236297A (zh) | 2020-11-25 | 2021-10-29 | 用於指出杭納氏病變之程式、已學習之模型及其生成方法 |
EP21898060.5A EP4252614A1 (en) | 2020-11-25 | 2021-11-25 | Program for indicating hunner lesions, trained model, and method for generating same |
PCT/JP2021/043293 WO2022114088A1 (ja) | 2020-11-25 | 2021-11-25 | ハンナ病変の指摘のためのプログラム、学習済みモデル及びその生成方法 |
KR1020237009542A KR20230110246A (ko) | 2020-11-25 | 2021-11-25 | 허너 병변의 지적을 위한 프로그램, 학습 완료 모델 및 그 생성 방법 |
CN202180063736.1A CN116261418A (zh) | 2020-11-25 | 2021-11-25 | 用于指示洪纳病变的程序、已学习模型及其生成方法 |
JP2022090661A JP2022111195A (ja) | 2020-11-25 | 2022-06-03 | ハンナ病変の指摘のためのプログラム |
US17/818,853 US20220392063A1 (en) | 2020-11-25 | 2022-08-10 | Program for indicating hunner lesion, learned model, and method for generating same |
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US (1) | US20220392063A1 (ja) |
EP (1) | EP4252614A1 (ja) |
JP (2) | JP7124041B2 (ja) |
KR (1) | KR20230110246A (ja) |
CN (1) | CN116261418A (ja) |
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JP2024008323A (ja) * | 2022-07-08 | 2024-01-19 | 国立研究開発法人産業技術総合研究所 | 学習用画像データ作成方法及びシステム |
CN115670347A (zh) * | 2022-09-22 | 2023-02-03 | 中国科学院苏州生物医学工程技术研究所 | 移动式食管内镜图像采集与质控*** |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
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JP2009066090A (ja) | 2007-09-12 | 2009-04-02 | Npo Comfortable Urology Network | 下部尿路障害を診断する方法 |
JP2017534322A (ja) | 2014-09-17 | 2017-11-24 | タリス バイオメディカル エルエルシー | 膀胱の診断的マッピング方法及びシステム |
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US7807074B2 (en) | 2006-12-12 | 2010-10-05 | Honeywell International Inc. | Gaseous dielectrics with low global warming potentials |
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- 2021-11-25 WO PCT/JP2021/043293 patent/WO2022114088A1/ja unknown
- 2021-11-25 CN CN202180063736.1A patent/CN116261418A/zh active Pending
- 2021-11-25 EP EP21898060.5A patent/EP4252614A1/en active Pending
- 2021-11-25 KR KR1020237009542A patent/KR20230110246A/ko unknown
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2009066090A (ja) | 2007-09-12 | 2009-04-02 | Npo Comfortable Urology Network | 下部尿路障害を診断する方法 |
JP2017534322A (ja) | 2014-09-17 | 2017-11-24 | タリス バイオメディカル エルエルシー | 膀胱の診断的マッピング方法及びシステム |
Non-Patent Citations (1)
Title |
---|
Hunner lesion versus non-Hunner lesion interstitial crystitis/bladder pain syndrome,International Journal of Urology,wiley,2019年05月30日,Volume 26, Issue S1,pp. 26-34,http: onlinelibrary.wiley.com/doi/epdf/10.1111/iju.13971,第28頁右欄第12行目-第29頁右欄第5行目 |
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CN116261418A (zh) | 2023-06-13 |
WO2022114088A1 (ja) | 2022-06-02 |
JP2022111195A (ja) | 2022-07-29 |
US20220392063A1 (en) | 2022-12-08 |
TW202236297A (zh) | 2022-09-16 |
KR20230110246A (ko) | 2023-07-21 |
EP4252614A1 (en) | 2023-10-04 |
JP2022083867A (ja) | 2022-06-06 |
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