🗞️ News - December 17, 2025

New Online Tool for Choosing AI Models for 3D Organ Imaging

New online tool aids in selecting AI models for 3D organ imaging, enhancing treatment accuracy for patients. 🩺💻

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New Online Tool for Choosing AI Models for 3D Organ Imaging

Overview

A research team from the Department of Electronics, Information and Bioengineering at the Politecnico di Milano, led by Dr. Andrea Moglia, has introduced an innovative online application. This tool assists healthcare professionals in selecting the most suitable Artificial Intelligence (AI) models for generating 3D images of individual organs, enhancing the accuracy and reliability of patient treatment.

Key Features of the Application
  • The app is designed for healthcare professionals, including technicians and doctors, to streamline the imaging process.
  • It allows users to start by selecting specific organs or broader anatomical areas such as the chest, neck, or abdomen.
  • Once an organ is selected, the app lists all available AI models tested on relevant image datasets, sorted by effectiveness.
  • Users can filter models based on their ability to generate images of tumors and lesions.
Efficiency in Medical Imaging

Dr. Moglia emphasized that this tool significantly improves the efficiency of selecting AI models for diagnostic imaging. It reduces the need for multiple attempts to achieve clear images, allowing hospitals to plan which AI models to adopt based on the frequency of operations performed on specific organs.

Types of AI Models Available

The application includes both generalist and organ-specific AI models. Generalist models, trained on diverse human body images, have shown effectiveness comparable to specialized models designed for specific organs. This represents a notable advancement in the field of medical imaging.

Impact on Clinical Practice

AI models have been utilized for imaging organs and lesions, a process known as segmentation. This technique allows for the delineation of structures in 2D images to create 3D reconstructions. By employing AI, the process becomes faster and minimizes human error.

Research Background

The development of this application stems from a study published in the journal Information Fusion, which explored various AI models for medical imaging.

Conclusion

This free online application is expected to democratize access to advanced AI tools, facilitating the adoption of precision imaging in healthcare and ultimately improving patient care.

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