Py3DFreeHandUS: a library for voxel-array reconstruction using Ultrasonography and attitude sensors

TL;DR

This paper introduces Py3DFreeHandUS, a Python library that combines ultrasonography and attitude sensors to reconstruct 3D models of body structures, offering a real-time alternative to traditional imaging methods.

Contribution

The paper presents a novel Python library that integrates US and optoelectronic data for 3D reconstruction of anatomical structures, enhancing clinical imaging capabilities.

Findings

Successful 3D reconstruction of body structures using the library

Calibration procedures improve reconstruction accuracy

Real-time processing enables clinical applications

Abstract

In medical imaging, there is a growing interest to provide real-time images with good quality for large anatomical structures. To cope with this issue, we developed a library that allows to replace, for some specific clinical applications, more robust systems such as Computer Tomography (CT) and Magnetic Resonance Imaging (MRI). Our python library Py3DFreeHandUS is a package for processing data acquired simultaneously by ultra-sonographic systems (US) and marker-based optoelectronic systems. In particular, US data enables to visualize subcutaneous body structures, whereas the optoelectronic system is able to collect the 3D position in space for reflective objects, that are called markers. By combining these two measurement devices, it is possible to reconstruct the real 3D morphology of body structures such as muscles, for relevant clinical implications. In the present research work, the different steps which allow to obtain a relevant 3D data set as well as the procedures for calibrating the systems and for determining the quality of the reconstruction.