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@article{196201,
        author = {VADAMA SURENDRA and Pagadala Srinivasu and TALLURI KRISHNA SANJAY and Nagoor Sharif and AYINAVELLI UDAYKIRAN},
        title = {Automated Kidney Stone Detection Using Image Processing Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {2165-2169},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196201},
        abstract = {Kidney stones are now a serious issue that, if not treated right away, can lead to complications and occasionally even require surgery to remove. Image processing can greatly increase the likelihood of accurately detecting stones well in advance. It has the propensity to produce accurate results and is an automatic method of finding the stone. Because kidney stones have low contrast and speckle noise, finding them via ultrasound imaging is a very difficult task. By using appropriate Image processing-MatLab approaches, this problem is solved. The speckle noise in the ultrasound image is first pre-processed using the image restoration technique. Stone placement detection was then performed using the reconstructed image.},
        keywords = {},
        month = {April},
        }