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 Hollow Core Photonic Crystal Fiber (HC-PCF) based sensor is presented for tumour 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 analysed 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 tumour detection and treatment. Result shows that DL have shown an efficiency of 95%, sensitivity as 92%, specificity as 93% and accuracy as 94 % which are more than that of CNN. Additionally, it 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.
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Analyzing Trends in Medical Imaging Using Intelligent Photonics
Published: 27 October 2023 by MDPI in 4th International Electronic Conference on Applied Sciences session Electrical, Electronics and Communications Engineering
Keywords: Medical Imaging, Intelligent Photonics, Deep Learning, Convolutional Neural Network, HPCF, Tumor Detection.