Development of anatomical phantoms for an ultra-low field magnetic resonance imaging system

In this work, we present the development of phantoms made out by anatomical models printed with a 3D printer and adequate them to fit an Ultra-Low Field Magnetic Resonance Imaging System, in order to obtain 2D images. It was used a machine learning algorithm to segment anatomical images from CT and MRI databases from three different organs, and therefore a 3D printer was used to build structures that can fit system’s bore and acquire images using basic acquisition sequences to obtain 2D images. The images obtained with the Ultra-Low Field MRI system, show the borders of the phantoms manufactured. This can help us to ensure that the contours from our phantoms can be appreciated with the imaging system, which can lead us to improve system’s hardware and imaging processing techniques for academic and research purposes.