CN111093525A - 光学相干断层图像处理方法 - Google Patents

光学相干断层图像处理方法 Download PDF

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CN111093525A
CN111093525A CN201880059686.8A CN201880059686A CN111093525A CN 111093525 A CN111093525 A CN 111093525A CN 201880059686 A CN201880059686 A CN 201880059686A CN 111093525 A CN111093525 A CN 111093525A
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anterior segment
image
iris
optical coherence
cornea
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赵云娥
黄锦海
于航
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Wenzhou Medical University
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/102—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for optical coherence tomography [OCT]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/0016—Operational features thereof
    • A61B3/0025—Operational features thereof characterised by electronic signal processing, e.g. eye models
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/13—Tomography
    • 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
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/149—Segmentation; Edge detection involving deformable models, e.g. active contour models
    • 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
    • G06T2207/10024—Color image
    • 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
    • G06T2207/10101—Optical tomography; Optical coherence tomography [OCT]
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30041—Eye; Retina; Ophthalmic

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
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  • Signal Processing (AREA)
  • Eye Examination Apparatus (AREA)

Abstract

本发明公开了一种光学相干断层图像处理方法，包括步骤：一、用光学相干断层技术采集眼前节断层图像，得到眼前节黑白图像；二、将眼前节黑白图像进行伪彩话处理及色彩空间转换，并进行叠加阈值二值化，区分出角膜、虹膜和晶状体潜在区域，再分别利用blob形状分析，获得角膜、虹膜和晶状体区域；三、利用构造学运算对步骤二获得的角膜、虹膜和晶状体区域进行斑点填充和坍缩处理；四、运用水平集算法对图像进行边界跟踪，精确跟踪出眼前节各部分表面边界，找到眼前节。本发明克服了全图运用水平集算法速度慢的瓶颈，实现了眼前节断层图像特征的实时提取、分析，为后续求得眼前节临床参数提供了可靠的基础数据。

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PCT国内申请，说明书已公开。

Claims (7)

  1. PCT国内申请，权利要求书已公开。
CN201880059686.8A 2018-08-07 2018-08-07 光学相干断层图像处理方法 Pending CN111093525A (zh)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116309661A (zh) * 2023-05-23 2023-06-23 广东麦特维逊医学研究发展有限公司 眼前节oct图像轮廓提取方法
CN116777794A (zh) * 2023-08-17 2023-09-19 简阳市人民医院 一种角膜异物图像的处理方法及系统

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101751603A (zh) * 2008-12-10 2010-06-23 东北大学 在线棒型材图像自动计数设备及方法
CN202350737U (zh) * 2011-10-09 2012-07-25 长安大学 一种基于matlab的发动机喷雾图像优化处理装置
CN104013384A (zh) * 2014-06-11 2014-09-03 温州眼视光发展有限公司 眼前节断层图像特征提取方法
CN104751474A (zh) * 2015-04-13 2015-07-01 上海理工大学 一种级联式快速图像缺陷分割方法
CN105761218A (zh) * 2016-02-02 2016-07-13 中国科学院上海光学精密机械研究所 光学相干层析成像的图像伪彩色处理方法
CN107133959A (zh) * 2017-06-12 2017-09-05 上海交通大学 一种快速的血管边界三维分割方法及系统

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8358819B2 (en) * 2005-06-24 2013-01-22 University Of Iowa Research Foundation System and methods for image segmentation in N-dimensional space
CN1900951A (zh) * 2006-06-02 2007-01-24 哈尔滨工业大学 基于数学形态学的虹膜图像柔性分区方法
JP5792967B2 (ja) * 2011-02-25 2015-10-14 キヤノン株式会社 画像処理装置及び画像処理システム
US9060717B2 (en) * 2012-02-02 2015-06-23 The Ohio State University Detection and measurement of tissue images
CN104050667A (zh) * 2014-06-11 2014-09-17 温州眼视光发展有限公司 瞳孔跟踪图像处理方法
US10229492B2 (en) * 2015-06-17 2019-03-12 Stoecker & Associates, LLC Detection of borders of benign and malignant lesions including melanoma and basal cell carcinoma using a geodesic active contour (GAC) technique
CN105894498A (zh) * 2016-03-25 2016-08-24 湖南省科学技术研究开发院 一种视网膜光学相干图像分割方法
CN106447682A (zh) * 2016-08-29 2017-02-22 天津大学 基于帧间相关性的乳腺mri病灶的自动分割方法
CN106530316B (zh) * 2016-10-20 2019-02-19 天津大学 综合眼底图像边缘信息和亮度信息的视盘分割方法
CN106846314B (zh) * 2017-02-04 2020-02-07 苏州比格威医疗科技有限公司 一种基于术后角膜oct影像数据的图像分割方法
CN107169975B (zh) * 2017-03-27 2019-07-30 中国科学院深圳先进技术研究院 超声图像的分析方法及装置
CN107016683A (zh) * 2017-04-07 2017-08-04 衢州学院 基于区域生长初始化的水平集海马图像分割方法
CN107330897B (zh) * 2017-06-01 2020-09-04 福建师范大学 图像分割方法及其系统
CN107909589B (zh) * 2017-11-01 2020-10-09 浙江工业大学 一种结合C-V水平集和GrabCut算法的牙齿图像分割方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101751603A (zh) * 2008-12-10 2010-06-23 东北大学 在线棒型材图像自动计数设备及方法
CN202350737U (zh) * 2011-10-09 2012-07-25 长安大学 一种基于matlab的发动机喷雾图像优化处理装置
CN104013384A (zh) * 2014-06-11 2014-09-03 温州眼视光发展有限公司 眼前节断层图像特征提取方法
CN104751474A (zh) * 2015-04-13 2015-07-01 上海理工大学 一种级联式快速图像缺陷分割方法
CN105761218A (zh) * 2016-02-02 2016-07-13 中国科学院上海光学精密机械研究所 光学相干层析成像的图像伪彩色处理方法
CN107133959A (zh) * 2017-06-12 2017-09-05 上海交通大学 一种快速的血管边界三维分割方法及系统

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116309661A (zh) * 2023-05-23 2023-06-23 广东麦特维逊医学研究发展有限公司 眼前节oct图像轮廓提取方法
CN116309661B (zh) * 2023-05-23 2023-08-08 广东麦特维逊医学研究发展有限公司 眼前节oct图像轮廓提取方法
CN116777794A (zh) * 2023-08-17 2023-09-19 简阳市人民医院 一种角膜异物图像的处理方法及系统
CN116777794B (zh) * 2023-08-17 2023-11-03 简阳市人民医院 一种角膜异物图像的处理方法及系统

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Application publication date: 20200501