brain2print AI powered web tool for creating 3D printable brain models

Area of Science:

• Medical imaging
• 3D printing
• Artificial intelligence

Background:

• Traditional methods for converting MRI scans to 3D models are complex and time-consuming.
• Existing tools often require multiple software installations and technical expertise.
• Limited accessibility hinders the use of 3D printing in education, clinical settings, and research.

Purpose of the Study:

• To introduce brain2print, an open-source, web-based application for converting T1-weighted MRI scans into 3D printable models.
• To leverage artificial intelligence (AI) for automated segmentation and mesh generation directly on the user's device.
• To provide a user-friendly, privacy-preserving, and accessible solution for creating 3D anatomical models.

Main Methods:

• Development of a web-based application, brain2print, utilizing AI algorithms.
• Implementation of on-device computation to process MRI data and preserve user privacy.
• Integration of drag-and-drop functionality for MRI scans and selection of AI segmentation models.
• Enabling customization of mesh complexity and structure for 3D printing.

Main Results:

• brain2print successfully converts T1-weighted MRI scans into 3D printable mesh models.
• The application performs all computations locally, ensuring data privacy and eliminating software installation requirements.
• The zero-footprint design ensures broad compatibility across various devices and browsers.
• The process is significantly faster and more user-friendly compared to prior methods.

Conclusions:

• brain2print offers a streamlined and efficient solution for generating 3D printable models from MRI data.
• The tool democratizes access to 3D printing for anatomical visualization in education, clinical practice, and research.
• By prioritizing privacy and ease of use, brain2print facilitates wider adoption of 3D printing technologies in neuroscience and medicine.