Analyzing Trends in Medical Imaging Using Intelligent Photonics †.

The integration of photonics and artificial intelligence (AI) has led to the emergence of intelligent photonics, which offers significant advancements in medical imaging. In this paper, a Photonic Crystal Fiber (PCF)-based sensor is presented for tumor detection. The finite element method is used to simulate the proposed sensor. By varying the geometrical parameters of the proposed sensor, an optimized sensor is proposed. Meanwhile, the latest AI techniques used in medical imaging, such as deep learning (DL) and convolutional neural networks (CNN), are also analyzed to improve upon the ability of the sensor. This paper highlights the potential of intelligent photonics in improving efficiency, sensitivity, specificity and accuracy of medical imaging, particularly in the areas of tumor detection and treatment. The results show that DL has an efficiency of 95%, and CNN has shown an accuracy of 98%. Additionally, this paper discusses the challenges and limitations that need to be addressed in order to fully realize the potential of these technologies. This paper demonstrates that the integration of photonics and AI has great potential to revolutionize medical imaging. [ABSTRACT FROM AUTHOR]