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An Investigation of AI Techniques for Detecting Kidney Stones in CT Scan Images Through Advanced Image Processing

Ranjit Barua

2024Advances in medical technologies and clinical practice book series11 citationsDOI

Abstract

Image processing techniques provide an automated and objective way to detect kidney stones in medical images, reducing the need for manual interpretation and potentially improving the accuracy and efficiency of diagnosis. It's important to note that the specific algorithms and methods used can vary depending on the type of medical imaging and the equipment employed for image acquisition. Kidney stone disease is increasingly prevalent today, primarily caused by the high concentration of minerals and salts in urine, resulting in the formation of hard deposits known as kidney stones. The gold standard for kidney stone diagnosis has shifted to computed tomography (CT). In this chapter, the authors present a concise overview of recent advancements in the diagnosis of kidney stones utilizing image processing techniques.

Topics & Concepts

Kidney stonesImage processingArtificial intelligenceComputer scienceKidney stone diseaseGold standard (test)Computed tomographyKidneyKidney diseaseTomographyRadiologyComputer visionMedicineImage (mathematics)SurgeryInternal medicineKidney Stones and Urolithiasis TreatmentsAdvanced X-ray and CT ImagingPediatric Urology and Nephrology Studies
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