用于光学相干断层扫描血管造影的自动脉络膜新生血管检测算法
Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography.
作者信息
Liu Li, Gao Simon S, Bailey Steven T, Huang David, Li Dengwang, Jia Yali
机构信息
Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, USA ; College of Physics and Electronics, Shandong Normal University, Jinan, China.
Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, USA.
出版信息
Biomed Opt Express. 2015 Aug 25;6(9):3564-76. doi: 10.1364/BOE.6.003564. eCollection 2015 Sep 1.
Abstract
Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area.
摘要
光学相干断层扫描血管造影术最近已被用于可视化年龄相关性黄斑变性患者的脉络膜新生血管（CNV）。CNV面积的识别和量化在临床上对于疾病评估很重要。本文提出了一种用于CNV面积检测的自动算法。它依靠去噪和显著性检测模型来克服诸如投影伪影和CNV异质性等问题。对7名参与者的扫描进行了定性和定量评估。该算法的结果与手动勾勒的CNV面积非常吻合。
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