Web-Based Video Analysis and Visualization of Magnetic Resonance Imaging Reports for Enhanced Patient Understanding - D. Shanthi, D. Shanthi; G. Ashok, G. Ashok; Vennela, Bontha; Reddy, K. Harika; P. Deekshitha, P. Deekshitha; Nandini, U. Bala Sri Bhavya (Journal of Neonatal Surgery, 2025)
Magnetic Resonance Imaging (MRI) is an age-old diagnostic imaging technique in modern medicine, but the technical nature of MRI reports makes patients incapable of understanding their own healthcare information. In this paper, an AI-based web portal fills this gap by translating and interpreting MRI reports in natural language processing and multimedia content. The system begins with the image or PDF upload process with the content text extracted with Tesseract OCR and PyMuPDF. Regular Expressions and NLP models—that include facebook/bart-large-cnn for summarization and KeyBERT for keyword extraction—are used by the system to break down medical jargon into plain language. Enrichment is also encouraged with the use of the Google Custom Search API to identify key words and related medical references. Final interpretation is also offered by way of interactive audio-visual content by virtue of the use of gTTS for voice-over and moviepy for video creation. The process encourages patient understanding, provides multilingual accessibility, and allows more open healthcare communication.