Imaging procedures in medicine are beneficial in diagnosing and treating a wide range of medical disorders. Because the images recorded by the many different imaging modalities are often complicated, image processing methods are required to improve their quality and get relevant information from them. Image processing has made it possible to construct computer-aided diagnostic (CAD) systems, which are designed to assist medical practitioners in detecting and identifying disorders. Isolating specific structures inside the body and following their evolution over time is now feasible because of recent advances in imaging techniques such as image segmentation and registration. Additionally, the use of image processing to build virtual and augmented reality environments has led to improvements in medical education and training and in the planning and execution of surgical procedures. This abstract focuses on how image processing has revolutionized medical imaging and made it possible for medical practitioners to identify and treat illnesses more efficiently.
The paper adeptly highlights the complexity of images generated by various medical imaging modalities and underscores the necessity of image processing methods to refine these images. The mention of computer-aided diagnostic (CAD) systems is particularly noteworthy, as it showcases the practical applications of image processing in supporting medical practitioners in the detection and identification of disorders.
To further enrich the paper, providing specific examples or case studies that demonstrate the practical impact of image processing in real-world medical scenarios would enhance the reader's understanding. Additionally, a brief discussion on the challenges or limitations associated with image processing in medical science could provide a balanced perspective.
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