Abstract
In the field of ophthalmology, optical coherence tomography (OCT) has proven to be a powerful imaging technique when it comes to diagnosing various eye-related diseases. This research article introduces a real-time automatic retinal layer segmentation algorithm based on intensity variation in the OCT images. The built algorithm is capable of detecting internal retinal layers like the internal limiting membrane (ILM), the retinal pigment epithelium (RPE) and the retinal nerve fiber layer (RNFL) with micrometer level precision, the algorithm uses openMP for parallelized computation for real-time visualization of the segmented retinal layers. The total execution time of the algorithm was evaluated using various image sizes and compared with the OCT frame rate to demonstrate the efficiency of real-time segmentation.
Highlights
When it comes to early diagnosis of diseases in the field of ophthalmology, optical coherence tomography (OCT) is seen as a well-established and reliable imaging technique
We have introduced a real-time automatic retinal layer segmentation algorithm based on intensity variation in the OCT images
The measurement of the macula is performed with the OCT images obtained from a 3-dimensional scan, and the dataset is of 800 x 600 pixels, and 300 frames were used for the layer segmentation process
Summary
When it comes to early diagnosis of diseases in the field of ophthalmology, optical coherence tomography (OCT) is seen as a well-established and reliable imaging technique. With the use of OCT imaging, it becomes possible to diagnose the disease by analyzing the internal morphology of the retinal layers When it comes to glaucoma and other ophthalmological disease diagnoses, the measurement of the thickness of the retina and the RNFL becomes a key factor [5]. In OCT images, the retinal thickness is measured by calculating the total distance between the ILM and RPE layers Calculation of these layer thickness is crucial for ophthalmology disease diagnosis and serves as an important parameter making the treatment planning. This method is most suitable to only identify the ILM layer This makes a real-time overall thickness measurement and segmentation of retinal layers a growing research field that has fascinated the researchers worldwide. The proposed algorithm can effectively identify the RPE, ILM, and RNFL layers, along with their total layer thickness measurement analysis
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