This paper presents an innovative and integrative application designed for the preprocessing and analysis of medical images, with a particular focus on edge detection and image filtering. The application aims to support diagnostic processes by enhancing image features critical to clinical interpretation. The actual version of the innovative Medical Image Analyzer (iMIA) platform includes two primary functional modules: Edge algorithms, which implements both classical and artificial intelligence related edge detection techniques, and Filters & Analysis, which applies spatial filters to improve contrast and reduce noise. By combining these techniques, the tool facilitates the identification of anatomical boundaries and regions of interest in medical scans, particularly CT images. COVID-19 Lung CT medical images were used to test the application and delivered promising results. The application provides an intuitive interface and modular structure, making it suitable for both educational and research purposes in medical image processing.