Ai-Powered Dicom Image Segmentation: A Collaborative Platform For Continuous Expert Feedback

This work presents the development of an interactive web platform that in-tegrates deep learning techniques for the segmentation of cardiac ultrasound (echocardiogram) images. The platform incorporates a Picture Archiving and Communication System (PACS) to facilitate the seamless visualization, an-notation, and automated processing of DICOM images. The web platform features an intuitive interface that allows healthcare professionals to inter-actively annotate medical images, providing feedback that directly informs model improvements. The system’s retraining workflow ensures that AI-driven segmentation remains adaptable to real-world clinical needs. These findings underscore the importance of iterative AI model refinement through expert feedback, paving the way for more reliable and personalized medical image analysis.