A study on the Application of Bio-Inspired Algorithms in the Diagnosis of Efficient Ultrasound Liver Images
Manish Kumar Yadav, Akshat Vikram Singh, Arun Kumar Singh, Shruti · 2022
Maintaining physical and mental well-being is a major concern for every person. Liver disease is one of the worst illnesses that affects people throughout. Modern hospitals have the latest in data collecting and transmission devices, allowing for smooth information exchange across different computerized systems. In spite of this, making a correct diagnosis of an illness has always been a vital part of the medical profession. Diseases of the liver are difficult to diagnose early on because the organ might appear healthy while nevertheless being severely damaged. Indeed, the patient’s life expectancy can be significantly improved with early detection of liver problems.Numerous artificial intelligence and optimization algorithms have lately earned a lot of attractiveness in medical diagnostics which are employed to identify the ailment using the gathered data. There has been a rise in the use of CAD (Computer Aided Diagnosis) techniques in the medical field as a result of their increased efficiency. Specialists in the creation of cutting-edge algorithms now guarantee a higher degree of accuracy in the detection and diagnosis of illnesses. As a result, using improvised algorithms can address the core problem of predicting and identifying the disease at an early stage.The research begins with an investigation of the integration of machine learning with classification optimization strategies. Due to its non-persistent nature, cheap cost, portability, and suitability for classification methods, ultrasound imaging is frequently employed in medical diagnostics. In this procedure, liver illness is classified using image processing techniques based on computer-aided design. In this research work, we have conducted a comprehensive study on the application of Bio-Inspired Algorithms in the Diagnosis of Efficient Ultrasound Liver Images. This evaluation was carried out using the Bio-Inspired Algorithms Liver Image Analysis. Additionally, this will assist other researchers in becoming aware of the research gaps as well as other comparable work done by other scientific organisations.