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BE1028516B1 - BIOMEDICAL IMAGE SEGMENTATION METHODS AND SYSTEMS INCLUDING AN ATTENTION GATED SKIP CONNECTION - Google Patents

BIOMEDICAL IMAGE SEGMENTATION METHODS AND SYSTEMS INCLUDING AN ATTENTION GATED SKIP CONNECTION

Info

Publication number
BE1028516B1
BE1028516B1 BE20205976A BE202005976A BE1028516B1 BE 1028516 B1 BE1028516 B1 BE 1028516B1 BE 20205976 A BE20205976 A BE 20205976A BE 202005976 A BE202005976 A BE 202005976A BE 1028516 B1 BE1028516 B1 BE 1028516B1
Authority
BE
Belgium
Prior art keywords
image segmentation
gated
attention
skip connection
biomedical image
Prior art date
Application number
BE20205976A
Other languages
French (fr)
Inventor
Akshayaa Vaidyanathan
Original Assignee
Oncoradiomics
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 Oncoradiomics filed Critical Oncoradiomics
Priority to BE20205976A priority Critical patent/BE1028516B1/en
Priority to PCT/EP2021/084462 priority patent/WO2022135895A1/en
Application granted granted Critical
Publication of BE1028516B1 publication Critical patent/BE1028516B1/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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • 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
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (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)
  • Image Processing (AREA)
  • Image Analysis (AREA)

Abstract

La présence invention révèle des méthodes et des systèmes de segmentation d'images biomédicales.Les méthodes comprennent de préférence une combinaison de U-Net et de ResNeXt avec une attention gated skip connection. D'autres applications privilégiées de l'ivention comprennent des étapes de supervision approfondie de la concaténation ou des cartes de caractéristiques suréchantillonnées à chaque étapes du décodeur.The present invention discloses methods and systems for biomedical image segmentation. The methods preferably include a combination of U-Net and ResNeXt with a gated attention skip connection. Other preferred applications of the invention include deep concatenation monitoring steps or oversampled feature maps at each decoder step.

BE20205976A 2020-12-23 2020-12-23 BIOMEDICAL IMAGE SEGMENTATION METHODS AND SYSTEMS INCLUDING AN ATTENTION GATED SKIP CONNECTION BE1028516B1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
BE20205976A BE1028516B1 (en) 2020-12-23 2020-12-23 BIOMEDICAL IMAGE SEGMENTATION METHODS AND SYSTEMS INCLUDING AN ATTENTION GATED SKIP CONNECTION
PCT/EP2021/084462 WO2022135895A1 (en) 2020-12-23 2021-12-06 Biomedical image segmentation methods and systems comprising an attention gated skip connection

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
BE20205976A BE1028516B1 (en) 2020-12-23 2020-12-23 BIOMEDICAL IMAGE SEGMENTATION METHODS AND SYSTEMS INCLUDING AN ATTENTION GATED SKIP CONNECTION

Publications (1)

Publication Number Publication Date
BE1028516B1 true BE1028516B1 (en) 2022-02-16

Family

ID=74853480

Family Applications (1)

Application Number Title Priority Date Filing Date
BE20205976A BE1028516B1 (en) 2020-12-23 2020-12-23 BIOMEDICAL IMAGE SEGMENTATION METHODS AND SYSTEMS INCLUDING AN ATTENTION GATED SKIP CONNECTION

Country Status (2)

Country Link
BE (1) BE1028516B1 (en)
WO (1) WO2022135895A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116258672B (en) * 2022-12-26 2023-11-17 浙江大学 Medical image segmentation method, system, storage medium and electronic equipment
CN117274185B (en) * 2023-09-19 2024-05-07 阿里巴巴达摩院(杭州)科技有限公司 Detection method, detection model product, electronic device, and computer storage medium

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3973508A1 (en) 2019-05-23 2022-03-30 DeepMind Technologies Limited Sampling latent variables to generate multiple segmentations of an image
US10755413B1 (en) 2020-02-24 2020-08-25 Qure.Ai Technologies Private Limited Method and system for medical imaging evaluation

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
BALAGOPAL ANJALI ET AL: "Fully automated organ segmentation in male pelvic CT images", PHYSICS IN MEDICINE & BIOLOGY, vol. 63, no. 24, 14 December 2018 (2018-12-14), pages 245015, XP055832326, Retrieved from the Internet <URL:http://iopscience.iop.org/article/10.1088/1361-6560/aaf11c> DOI: 10.1088/1361-6560/aaf11c *
KEARNEY VASANT ET AL: "Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision", PHYSICS IN MEDICINE & BIOLOGY, vol. 64, no. 13, 2 July 2019 (2019-07-02), pages 135001, XP055832325, Retrieved from the Internet <URL:https://iopscience.iop.org/article/10.1088/1361-6560/ab2818> DOI: 10.1088/1361-6560/ab2818 *
KHANH TRINH LE BA ET AL: "Enhancing U-Net with Spatial-Channel Attention Gate for Abnormal Tissue Segmentation in Medical Imaging", APPLIED SCIENCES, vol. 10, no. 17, 19 August 2020 (2020-08-19), pages 5729, XP055832313, ISSN: 2076-3417, DOI: 10.3390/app10175729 *
SCHLEMPER JO ET AL: "Attention gated networks: Learning to leverage salient regions in medical images", MEDICAL IMAGE ANALYSIS, vol. 53, 1 April 2019 (2019-04-01), GB, pages 197 - 207, XP055832320, ISSN: 1361-8415, Retrieved from the Internet <URL:https://www.sciencedirect.com/science/article/pii/S1361841518306133/pdfft?md5=63d7697ccc0f3783ce7e023a308588c1&pid=1-s2.0-S1361841518306133-main.pdf> DOI: 10.1016/j.media.2019.01.012 *
XIAOCONG CHEN ET AL: "Residual Attention U-Net for Automated Multi-Class Segmentation of COVID-19 Chest CT Images", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 12 April 2020 (2020-04-12), XP081642988 *

Also Published As

Publication number Publication date
WO2022135895A1 (en) 2022-06-30

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FG Patent granted

Effective date: 20220216