• Dr.M.REVATHI

Deep learning is an improved method for analysing medical images for better performance.It has been successfully applied in target detection, segmentation, classification and registration. The development of deep learning in the medical field depends on the accumulation of medical big data, while the medical data itself has multi-modal characteristics, which provides a large amount of rich data for deep learning. In recent years, various types of medical image processing and recognition have adopted deep learning techniques in fundus images, endoscopic images, CT/MRI images, ultrasound images, pathological images. Deep learning technique is mainly used in classification and segmentation in medical images. This paper describes, a survey on four deep learning techniques such as Convolution Neural Network(CNN), Recurrent Neural Network (RNN), Generative Adversarial Neural network (GAN) and Self Organizing Map (SOM) for medical image analysis.

KEYWORDS: Deep Learning, CNN, RNN, GAN, and SOM.

"A Recent Survey on Deep Learning Techniques in Medical Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.g386-g394, March-2025, Available :http://www.jetir.org/papers/JETIR2503644.pdf

"A Recent Survey on Deep Learning Techniques in Medical Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppg386-g394, March-2025, Available at : http://www.jetir.org/papers/JETIR2503644.pdf