CN115136192A - 对模型的输入实例的分布外检测 - Google Patents

对模型的输入实例的分布外检测 Download PDF

Info

Publication number
CN115136192A
CN115136192A CN202180015890.1A CN202180015890A CN115136192A CN 115136192 A CN115136192 A CN 115136192A CN 202180015890 A CN202180015890 A CN 202180015890A CN 115136192 A CN115136192 A CN 115136192A
Authority
CN
China
Prior art keywords
model
ood
auxiliary
input
pixel
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
CN202180015890.1A
Other languages
English (en)
Chinese (zh)
Inventor
N·佩佐蒂
D·马弗罗伊迪斯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips NV
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 Koninklijke Philips NV filed Critical Koninklijke Philips NV
Publication of CN115136192A publication Critical patent/CN115136192A/zh
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/243—Classification techniques relating to the number of classes
    • G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • 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]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06T2207/30168—Image quality inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Multimedia (AREA)
  • Medical Informatics (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Image Analysis (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
CN202180015890.1A 2020-02-21 2021-02-05 对模型的输入实例的分布外检测 Pending CN115136192A (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP20158708.6 2020-02-21
EP20158708.6A EP3869401A1 (en) 2020-02-21 2020-02-21 Out-of-distribution detection of input instances to a model
PCT/EP2021/052750 WO2021165053A1 (en) 2020-02-21 2021-02-05 Out-of-distribution detection of input instances to a model

Publications (1)

Publication Number Publication Date
CN115136192A true CN115136192A (zh) 2022-09-30

Family

ID=69723854

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202180015890.1A Pending CN115136192A (zh) 2020-02-21 2021-02-05 对模型的输入实例的分布外检测

Country Status (5)

Country Link
US (1) US20230377314A1 (enExample)
EP (2) EP3869401A1 (enExample)
JP (1) JP7768136B2 (enExample)
CN (1) CN115136192A (enExample)
WO (1) WO2021165053A1 (enExample)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021189130A1 (en) * 2020-03-24 2021-09-30 Olympus NDT Canada Inc. Compressive sensing for full matrix capture
WO2022108912A1 (en) * 2020-11-23 2022-05-27 Subtle Medical, Inc. Automated medical image quality control system
US12387085B2 (en) * 2021-05-21 2025-08-12 Samsung Electronics Co., Ltd. Deep learning device and system including the same
KR102567558B1 (ko) * 2021-09-16 2023-08-16 광주과학기술원 Ood 객체 탐지 방법 및 시스템
WO2023154573A1 (en) * 2022-02-14 2023-08-17 Bostongene Corporation Machine learning techniques for tertiary lymphoid structure (tls) detection
CN114565759A (zh) * 2022-02-22 2022-05-31 北京百度网讯科技有限公司 图像语义分割模型优化方法、装置、电子设备及存储介质
JP2024032098A (ja) * 2022-08-29 2024-03-12 沖電気工業株式会社 情報処理装置、情報処理方法およびプログラム
EP4428762A1 (en) * 2023-03-07 2024-09-11 Robert Bosch GmbH Determining whether a given input record of measurement data is covered by the training of a trained machine learning model
KR102968038B1 (ko) * 2025-08-11 2026-05-20 중앙대학교 산학협력단 불확실성을 기반으로 분포 외 객체를 식별하기 위한 방법, 이를 수행하는 컴퓨팅 장치 및 그의 동작 방법

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109223016A (zh) * 2018-07-18 2019-01-18 江苏影医疗设备有限公司 Ct成像方法及成像设备
CN109344759A (zh) * 2018-06-12 2019-02-15 北京理工大学 一种基于角度损失神经网络的亲属识别方法

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5331550A (en) * 1991-03-05 1994-07-19 E. I. Du Pont De Nemours And Company Application of neural networks as an aid in medical diagnosis and general anomaly detection
RU2721078C2 (ru) * 2015-04-23 2020-05-15 Конинклейке Филипс Н.В. Сегментация анатомической структуры на основе модели
US10706327B2 (en) 2016-08-03 2020-07-07 Canon Kabushiki Kaisha Information processing apparatus, information processing method, and storage medium
JP6585654B2 (ja) 2017-05-01 2019-10-02 日本電信電話株式会社 判定装置、分析システム、判定方法および判定プログラム
JP7020156B2 (ja) 2018-02-06 2022-02-16 オムロン株式会社 評価装置、動作制御装置、評価方法、及び評価プログラム
WO2019167884A1 (ja) 2018-02-28 2019-09-06 富士フイルム株式会社 機械学習方法及び装置、プログラム、学習済みモデル、並びに判別装置
US11010902B2 (en) 2018-06-04 2021-05-18 University Of Central Florida Research Foundation, Inc. Capsules for image analysis
KR101940029B1 (ko) * 2018-07-11 2019-01-18 주식회사 마키나락스 어노말리 디텍션
CN114127747B (zh) * 2019-06-05 2025-09-09 谷歌有限责任公司 用于分布外检测的似然比
US20210142160A1 (en) * 2019-11-08 2021-05-13 Nvidia Corporation Processor and system to identify out-of-distribution input data in neural networks
EP3862927A1 (en) * 2020-02-05 2021-08-11 Another Brain Anomaly detector, method of anomaly detection and method of training an anomaly detector

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109344759A (zh) * 2018-06-12 2019-02-15 北京理工大学 一种基于角度损失神经网络的亲属识别方法
CN109223016A (zh) * 2018-07-18 2019-01-18 江苏影医疗设备有限公司 Ct成像方法及成像设备

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
保罗·伯格曼等: ""无知的学生：基于判别式潜在嵌入的学生-教师异常检测"", ARXIV.ORG，康奈尔大学图书馆, 6 November 2019 (2019-11-06) *

Also Published As

Publication number Publication date
JP7768136B2 (ja) 2025-11-12
EP3869401A1 (en) 2021-08-25
EP4107662A1 (en) 2022-12-28
WO2021165053A1 (en) 2021-08-26
JP2023515367A (ja) 2023-04-13
US20230377314A1 (en) 2023-11-23

Similar Documents

Publication Publication Date Title
JP7768136B2 (ja) モデルへの入力インスタンスの分布外検出
EP3633601B1 (en) Patient-specific deep learning image denoising methods and systems
EP3716214B1 (en) Medical image processing apparatus and method for acquiring training images
US10043088B2 (en) Image quality score using a deep generative machine-learning model
US12033247B2 (en) Three-dimensional shape reconstruction from a topogram in medical imaging
US10991092B2 (en) Magnetic resonance imaging quality classification based on deep machine-learning to account for less training data
US10387765B2 (en) Image correction using a deep generative machine-learning model
US10489907B2 (en) Artifact identification and/or correction for medical imaging
US11039805B2 (en) Deep learning based estimation of data for use in tomographic reconstruction
US20190385738A1 (en) Characterization of amount of training for an input to a machine-learned network
CN109993726A (zh) 医学图像的检测方法、装置、设备和存储介质
EP3895121A1 (en) System and method for providing stroke lesion segmentation using conditional generative adversarial networks
US12272034B2 (en) Systems and methods for background aware reconstruction using deep learning
US12567235B2 (en) Visual explanation of classification
CN110268441A (zh) 获得物体的多个部件的3d模型数据的方法
WO2024243250A2 (en) Parallel denoising diffusion probabilistic model-based tomographic image reconstruction from sparse projections
Frotscher et al. Unsupervised anomaly detection in medical imaging using aggregated normative diffusion
US20220292673A1 (en) On-Site training of a machine-learning algorithm for generating synthetic imaging data
CN112927196B (zh) 钙化积分方法及装置
Karthik et al. Improving Clinical Diagnosis Performance with Automated X-ray Scan Quality Enhancement Algorithms.

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20220930