BACKGROUND. The evaluation of brain maturation and neuronal migration process is difficult to carry out on ultrasound. In particular, the measurement of sulci and gyri dimensions (depth and length) depends on the experience of the operator and quality of the ultrasound imaging, leading to low reproducibility. Recently, medical image processing techniques based on deep learning have been successfully applied to analysis and segmentation of key structures in obstetric ultrasound.
OBJECTIVE. To develop a tool to automatically measure gyri and sulci depth/areas to allow quantitative assessment of consistency with the gestational age. See attached picture.
METHODS. Image processing methods (possibly based on deep learning) shall be devised to automatically identify and segment sulci and gyri in ultrasound images. This will be based on a set of volumes of the fetal brain acquired axially and coronally, from which navigation clips could be extracted for processing. Once the sulci and gyri are recognized and segmented, the software shall automatically perform their measurement. These measurements will be assessed by comparing them to measurements performed by an expert operator.
PARTNERS INVOLVED: Istituto Italiano di Tecnologia (IIT), Istituto Giannina Gaslini, Università Politecnica delle Marche.
Supervisors: Dr. Sara Moccia, Prof. Emanuele Frontoni (UNIVPM), Leonardo S. Mattos, PhD (IIT), M.D. Dario Paladini (Istituto Giannina Gaslini)
Skills that will be acquired: Programming (Python, MATLAB)
Contacts: {e.frontoni, s.moccia}@univpm.it
The candidate will spend part of the research period in the IIT labs of the Department of Advanced Robotics.
Istituto Italiano di Tecnologia (IIT) (https://www.iit.it/) is a Foundation governed by Articles 14 et seq of the Italian Civil Code, established by Legislative Decree 269/03, converted by Law no. 326/2003 (Article 4 of the Statute), and financed by the State to conduct scientific research in the public interest, for the purpose of technological development.
IIT aims to promote excellence in basic and applied research and to promote the development of the national economy.
