Optical Coherence Tomography Images Final Year Projects with Source Code
Optical Coherence Tomography Images Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Optical Coherence Tomography Images projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.
Optical Coherence Tomography Images Final Year Projects
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A Deep Ensemble Learning-Based CNN Architecture for Multiclass Retinal Fluid Segmentation in OCT Images
This project uses eye scan images to detect and outline fluid-filled cysts inside the retina. It trains a deep learning model to automatically find these cysts, which normally takes doctors a lot of time to do by hand. The system can identify different types of cysts and helps doctors understand eye diseases better. It also performs better than many existing methods. -
Multimodal Deep Learning Model of Predicting Future Visual Field for Glaucoma Patients
This project aims to predict how glaucoma will affect a patient’s vision in the future. It uses a deep learning model that looks at past vision test results and eye scan images to make predictions. The system combines image analysis with previous test data to improve accuracy. It also identifies and handles noisy or unreliable data, making the predictions more reliable for monitoring glaucoma progression.
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Optical Coherence Tomography Images Project Synopsis & Presentation
Final Year Projects helps prepare Optical Coherence Tomography Images project synopsis, including problem statement, objectives, existing system, disadvantages, proposed system, advantages and research motivation. We provide PPT slides, tutorials, and full documentation for presentations.
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