X-ray AI Radiologist -Advanced Chest X-ray Analysis

analysis of x-ray image
report full in one screen
report part 2
front page
patient information entry
report part 1
report part 3

Inspiration We were inspired by the need to improve diagnostic accuracy and efficiency in radiology, especially for busy clinicians who must review large volumes of chest X-rays. By harnessing the power of generative AI and modern web technologies, we aimed to build a tool that could support medical professionals and reduce the risk of missed diagnoses.

What it does The application uses AI to perform comprehensive analysis of chest X-rays, covering lung fields, cardiac silhouette, mediastinal structures, pleural spaces, bones, and soft tissues. It detects a wide range of pathologies, including pneumonia, tuberculosis, malignancies, interstitial lung disease, COPD, pulmonary edema, atelectasis, foreign bodies, and congenital abnormalities. The tool generates structured reports and provides a user-friendly interface for medical professionals.

How we built it We developed the tool on the blod.new platform using HTML and TypeScript for the frontend. backend NODE.JS The core AI functionality leverages Generative AI and the Gemini 2.0 API for advanced image analysis and report generation. The workflow involves image upload, preprocessing, AI-driven analysis (with systematic evaluation of all chest structures and pathologies), and the creation of a detailed report. The interface was designed to be intuitive and efficient, fitting seamlessly into clinical workflows.

Challenges we ran into Integrating Gemini 2.0 API: Ensuring smooth communication between our web application and the Gemini API required careful handling of authentication, data formats, and error management.

Performance Optimization: Balancing the speed of AI inference with the complexity of chest X-ray analysis was challenging, especially on web-based platforms.

User Interface Design: Creating an interface that is both powerful and easy to use for medical professionals required multiple iterations and feedback from clinicians.

Data Privacy: Implementing robust measures to protect patient data during upload and analysis was essential.

Accomplishments that we're proud of We are proud to have successfully built a comprehensive chest X-ray analysis tool on the blod.new platform, using cutting-edge technologies like Generative AI and Gemini 2.0. Our application stands out for its broad pathology coverage, intuitive interface, and seamless integration with clinical workflows. The ability to generate detailed, structured reports directly from the web browser is a significant achievement.

What I learned Through this project, we learned how to effectively integrate advanced AI APIs into web applications, optimize performance for medical imaging, and design user interfaces tailored to clinicians’ needs. We also gained valuable experience in handling sensitive medical data and ensuring compliance with privacy regulations.

What's next for AI Chest X-ray Analysis Tool I plan to:

Expand pathology detection to include more rare and complex conditions.

Enhance the user interface with advanced visualization tools and interactive features.

Integrate multi-modal data (such as clinical notes and lab results) for richer analysis.

Pursue regulatory approvals for clinical use.

Explore real-world validation in diverse healthcare settings to further improve accuracy and usability.