Intelligent chronic kidney stone disease detection from ct images using deep learning techniques

Abstract

In recent days, many diseases arise due to the changes in life styles and newlinefood habits. Based on the diagnosis and detection, some diseases may be cured newlineand some diseases may not be cured. Many Computers Assisted Diagnosis newlinesystems are available to detect the diseases in early stage itself to avoid the newlineseverity caused by the disease. Among these, one of the diseases which need an newlineearly detection was Kidney Stone Detection (KSD). Kidney Stone (KS) is a newlinewidely causing health issue occurred with severe pain and it needs more newlineattention. Detection of stones in kidney accurately in CT imageries is essential newlinefor effective medical intervention. Currently, many systems are available to newlinedetect the KS in an early stage without any human interruptions. But still, the newlineis a requirement for more efficient system to diagnose the KS disease. newlineAutomatic kidney stone detection is essential for various reasons. First newlineand foremost reason is that it enables early detection and prevention, which newlinehelps to identify KS before it causes excruciating pain and potentially serious newlinecomplications, like infections in the urinary tract, and may result in permanent newlinekidney damage. It also reduces diagnostic delays, as traditional methods often newlinerequire the presence of symptoms for diagnosis. This means automatic newlinedetection can expedite the process, allowing for timelier treatment. For earlier newlinedetection, diagnostic methods like CT scans are required. By streamlining the newlinediagnostic process, automatic detection promotes the efficient use of healthcare newlineresources, ultimately saving time and costs. newline