AI Engineering - Richard

Project’s dates

• Start Date - 08/04/2025
• Estimated End Date - 27/06/2025
• Actual End Date - [Actual End Date]

Medical Report Generation from Image Analysis Outputs

Problem Many image analysis algorithms and tools are used daily in the radiology workflow, while AI seems to be most promising for image analysis. AI Applications usually produce outputs in PDF, DICOM format, or a combination, as classification and segmentation are common tasks in medical image analysis. The additional images are stored and reviewed in the PACS, leading to an increased workload for radiologists when creating the medical report for referring physicians.

Solution

Support Radiologists by organizing multiple image analysis applications: Use the Image Analysis - Output (e.g. vertebral lesion detection) to generate a professional text section that describes and summarizes the findings for use in the medical report, following the RSNA Guidelines. 1. Anonymization 2. Preprocessing 3. OpenAI API generates structured output The intended use is in the medical reporting workflow, to help organize image analysis AI applications.

MVP-Workflow:

Project Folder Structure

Features:

• Add optional section that describes “Techniques”-part
• German and English languages available for report text
• Offer multiple styles

References:

Structured Reporting:

Github repo

[Enter github repo link]

GitHub - RichardNur/medimage2report: Convert PDF outputs from radiology AI tools into RSNA-compliant report text.

Convert PDF outputs from radiology AI tools into RSNA-compliant report text. - RichardNur/medimage2report

github.com

Database Schema

PROJECT: Generate Medical Report Text from Image Analysis - PDF

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Main Topics of Learning Materials

• Fundamentals of AI, Machine Learning, LLM’s
• Evolution of AI - History of Machine Learning
• What changed with LLM’s - ChatGPT Revolution
• Current market leads and differences between them
• Natural Language Processing
• Data Preprocessing
• Data Cleaning
• API Integration with AI models
• Structured Output
• Prompt Engineering
• GenAI Ethics
• Advanced GenAI
• Retrieval Augmented Generation (RAG)

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