• Neha Khandelwal
• Raju Kamble
• Sonam Rani
• Sarvesh Mamidwar

The detection of kidney stones is an important task in medical imaging. In recent years, image processing and deep learning techniques have shown great potential in medical image analysis. This paper presents an approach for kidney stone detection using image processing and deep learning. The proposed method consists of two main stages: image pre-processing and deep learning-based detection. In the pre-processing stage, images are pre-processed to enhance the features that are important for kidney stone detection. In the detection stage, a deep learning model is trained on the pre-processed images to detect the presence of kidney stones. The performance of the proposed method is evaluated using a dataset of kidney stone images. Experimental results show that the proposed method achieves high accuracy in kidney stone detection and outperforms traditional image processing techniques. The proposed method has the potential to be used in clinical settings for early detection and diagnosis of kidney stones.

KIDNEY STONE DETECTION USING IMAGE PROCESSING AND DEEP LEARNING

"KIDNEY STONE DETECTION USING IMAGE PROCESSING AND DEEP LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.385-392, May-2023, Available :http://www.jetir.org/papers/JETIRFX06068.pdf

"KIDNEY STONE DETECTION USING IMAGE PROCESSING AND DEEP LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp385-392, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06068.pdf