OCTA will reveal morphological changes of retinal vessels associated with a wide range of retinal diseases and has shown its potential clinical applications in facilitating monitoring and diagnosis of glaucoma ( 5), diabetic retinopathy ( 6), artery and vein occlusions ( 7), and age-related macular degeneration (AMD) ( 8), to name only the most widely occurring ones. Figure 1B demonstrates one high-quality retinal OCTA image sample. The accuracy of a computer-aided diagnosis system is highly dependent on the quality of pre-processing as errors can be propagated and accumulated due to poor imaging quality ( 2).Īs a functional extension of optical coherence tomography (OCT), OCT Angiography (OCTA) is a new emerging non-invasive imaging modality that enables observation of microvasculatures up to capillary level ( 3, 4). However, stripe artifacts or poor contrast often occur during the medical image acquisition process ( 1). Medical images with clean presentation, adequate contrast and informative details are essential in medical image analysis for clinical applications: e.g., tissue segmentation, and disease diagnosis. Our results show that the proposed framework yields a promising enhancement performance, which enables both conventional and deep learning-based vessel segmentation methods to produce improved results after enhancement of both retina and AS-OCTA modalities. Results and discussion: To evaluate the effectiveness of the proposed method, we apply the proposed framework to two synthetic OCTA datasets and a real AS-OCTA dataset. The vasculatures in acquired AS-OCTA images usually exhibit poor contrast, so we use a Perceptual Structure Generative Adversarial Network (PS-GAN) to enhance the de-striped AS-OCTA image in the re-enhancing stage, which combined cyclic perceptual loss with structure loss to achieve further image quality improvement. We introduce a new de-striping objective function in a Stripe Removal Net (SR-Net) to suppress the stripe noise in the original image. Methods: In this work, we propose a two-stage framework that comprises a de-striping stage and a re-enhancing stage, with aims to remove stripe noise and to enhance blood vessel structure from the background. These issues lead to incomplete vasculature maps that in turn makes it hard to make accurate interpretation and subsequent diagnosis. However, poor imaging quality, such as stripe artifacts and low contrast, is common in the acquired OCTA and in particular Anterior Segment OCTA (AS-OCTA) due to eye microtremor and poor illumination conditions. Introduction: Optical Coherence Tomography Angiography (OCTA) is a new non-invasive imaging modality that gains increasing popularity for the observation of the microvasculatures in the retina and the conjunctiva, assisting clinical diagnosis and treatment planning. 3Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, China.2Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.1School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing, China.Juan Cao 1 † Zihao Xu 1,2 † Mengjia Xu 3 * Yuhui Ma 2 * Yitian Zhao 2
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