Optical coherence tomography angiography (OCT-A) is a novel non-invasive imaging technique that provide the visualization of retinal microvasculature. However, the quantification and evaluation of OCT-A are still a challenge for the diagnosis for ophthalmology. Deep convolutional neural network (CNN) architectures were initially designed for the task of natural image classification, delivering promising precision in computer vision tasks and recent research has applied deep CNN to biomedical image processing tasks and produces impressive outcomes. However, so far, there is no report relating to the application of large deep neural networks on a small annotated OCT-A dataset. We collected and annotated OCT-A datasets that contain diabetic retinopathy (DR), uveitis, dry age-related macular degeneration (AMD) patients, and normal cases. We propose a transfer learning CNN model for automated disease classification using clinical OCT-A images. The CNN model is pre-trained on the ImageNet dataset and fine-tuned the top feedforward layers of the model to fit the classification task during the training process. The proposed approach can offer a real-time evaluation and discrimination of retinal pathologies with a depth-encoded OCT-A projected image. Our results show great accuracy of transfer learning CNN model on the classification task with the limited dataset. The CNN model with the pre-trained weights has better performance in comparison with an SVM using HOG feature approach.
KEYWORDS: Optical coherence tomography, Visualization, Amplitude modulation, Angiography, In vivo imaging, Signal to noise ratio, Photons, Tissues, Scattering, Imaging systems
The choriocapillaris (CC) plays an essential role in maintaining the normal functions of the human eye. There is increasing interest in the community to develop an imaging technique for visualizing the CC, yet this remains underexplored due to technical limitations. We propose an approach for the visualization of the CC in humans via a complex signal-based optical microangiography (OMAG) algorithm, based on commercially available spectral domain optical coherence tomography (SD-OCT). We show that the complex signal-based OMAG was superior to both the phase and amplitude signal-based approaches in detailing the vascular lobules previously seen with histological analysis. With this improved ability to visualize the lobular vascular networks, it is possible to identify the feeding arterioles and draining venules around the lobules, which is important in understanding the role of the CC in the pathogenesis of ocular diseases. With built-in FastTrac™ and montage scanning capabilities, we also demonstrate wide-field SD-OCT angiograms of the CC with a field of view at 9×11 mm2.
To investigate the application of wide field OCT angiography (OCTA) in living human eye. Normal and pathologic eyes
were recruited and imaged by a 1060 nm swept source OCTA system with A-line speed of 100 kHz provided by Carl
Zeiss Meditec. Inc.. Wide field OCTA images were generated in a single scan within 5 seconds based on the tracking
capability installed in the system with 9 x 9 mm2 and 12 x 12 mm2 field of view and sampled by 500 A-lines x 500 Bframes
with 2 repetitions in the same location for one 3D data. Complex optical microangiography (OMAG) algorithm
was used to extract the blood flow information. The en face maximum projection provided by the device was used to
generate 2-dimensional angiograms of different layers and color-code images. Wide field en face OCTA images of
different macular diseases showed a great agreement with fluorescein angiography (FA). Meanwhile, OCTA provides
depth-resolved information and detailed vascular images of venous occlusion and DR patients in far peripheral region,
and choroidal vessels imaging in serpiginous choroidopathy patient, providing a better visualization of vascular network
compared to FA.
Optical coherence tomography angiography (OCTA) is clinically useful for the qualitative assessment of the macular microvasculature. However, there is a need for comprehensive quantitative tools to help objectively analyze the OCT angiograms. Few studies have reported the use of a single quantitative index to describe vessel density in OCT angiograms. In this study, we introduce a five-index quantitative analysis of OCT angiograms in an attempt to detect and assess vascular abnormalities from multiple perspectives. The indices include vessel area density, vessel skeleton density, vessel diameter index, vessel perimeter index, and vessel complexity index. We show the usefulness of the proposed indices with five illustrative cases. Repeatability is tested on both a healthy case and a stable diseased case, giving interclass coefficients smaller than 0.031. The results demonstrate that our proposed quantitative analysis may be useful as a complement to conventional OCTA for the diagnosis of disease and monitoring of treatment.
To investigate the application of optical microangiography (OMAG) in living human eye. Patients with different macular diseases were recruited, including diabetic retinopathy (DR), geographic atrophy (GA), retinitis pigmentosa (RP), and venous occlusion, et al. Wide field OCT angiography images can be generated by montage scanning protocol based on the tracking system. OMAG algorithm based on complex differentiation was used to extract the blood flow and removed the bulk motion by 2D cross-correlation method. The 3D angiography was segmented into 3 layers in the retina and 2 layers in the choroid. The en-face maximum projection was used to obtain 2-dimensional angiograms of different layers coded with different colors. Flow and structure images were combined for cross-sectional view. En face OMAG images of different macular diseases showed a great agreement with FA. Meanwhile, OMAG gave more distinct vascular network visions that were less affected by hemorrhage and leakage. The MAs were observed in both superficial and middle retinal layers based on OMAG angiograms in different layers of DR patients. The contour line of FAZ was extracted as well, which can be quantitative the retinal diseases. For GA patient, the damage of RPE layer enhanced the penetration of light and enabled the acquisition of choriocapillaries and choroidal vessels. The wide field OMAG angiogram enabled the capability of capturing the entire geographic atrophy. OMAG provides depth-resolved information and detailed vascular images of DR and GA patients, providing a better visualization of vascular network compared to FA.
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