At AIAI Lab, we leverage Optical Coherence Tomography (OCT) and artificial intelligence (AI) to develop advanced solutions for plant disease detection. OCT imaging provides high-resolution, non-invasive structural images of plant tissues, allowing us to detect early signs of disease at the microscopic level. This technique can reveal subtle changes in plant cells and tissues, such as leaf structure, vascular health, and root systems, that are often invisible to the naked eye or traditional imaging methods.

By integrating AI algorithms, we automate the analysis of large OCT datasets, significantly improving the speed and accuracy of disease identification. AI models trained on healthy and diseased plant images can quickly classify conditions, predict disease progression, and even suggest interventions. This combination of OCT imaging and AI-driven analysis enhances early detection, enabling timely treatment and preventing the spread of diseases, which is critical for agriculture productivity and sustainability.

Our work aims to empower farmers and agricultural stakeholders with precise, real-time insights, fostering healthier crops and reducing reliance on chemical treatments.

Optical Coherence Tomography (OCT) is gaining traction in various medical fields for its ability to provide detailed, non-invasive imaging. In dermatology, OCT helps detect skin cancers and assess lesion depth without biopsies. In cardiology, it visualizes coronary arteries, assisting in diagnosing plaque buildup and guiding stent placement. OCT is also used in oncology to define tumor margins during surgeries, and in respiratory medicine, it aids in imaging airway structures for conditions like COPD. These applications enhance diagnosis and treatment precision across multiple medical specialties.