Thesis Project Form
Title (tentative): Development of client-based application for the support of epilepsy surgery| Thesis advisor(s): Fato Marco Massimo, Ing. Massimiliano Izzo (Gaslini) - Ing. Gabriele Arnulfo (DIBRIS) | E-mail: |
| Address: Via All'Opera Pia, 13 - 16145 Genova | Phone: (+39) 010 33 52789 |
Description
Motivation and application domain
Drug-resistant (i.e., symptoms are not pharmacologically controlled) epilepsy is treated with the surgical ablation of the putative seizure onset zone. The complex planning of such invasive approach require the integration of multimodal data such as MRIs, CT scans as well as electrophysiological data. In such a scenario a digital repository able to store, query and analyse multimodal data would ease the entire process of surgical intervention planning
General objectives and main activities
The general objectives and activities are:
1. design and configure the data types required by the project (patient, imaging, signals,...)
2. develop and test dedicated modules to store and retrieve bulk data (i.e. files) on the platform
3. integrate new modules with an advanced visualization system used in clinical process
1. design and configure the data types required by the project (patient, imaging, signals,...)
2. develop and test dedicated modules to store and retrieve bulk data (i.e. files) on the platform
3. integrate new modules with an advanced visualization system used in clinical process
Training Objectives (technical/analytical tools, experimental methodologies)
1. Object-oriented programming in C++/Python
2. Development, installation, and management of a complex multi-module biomedical platform on a Linux server
3. Schemaless (JSON-based) management of heterogenous biomedical metadata in a relational database (PostgreSQL)
4. Data analysis, using SQL analytics functions or machine learning techniques
2. Development, installation, and management of a complex multi-module biomedical platform on a Linux server
3. Schemaless (JSON-based) management of heterogenous biomedical metadata in a relational database (PostgreSQL)
4. Data analysis, using SQL analytics functions or machine learning techniques
Place(s) where the thesis work will be carried out: DIBRIS
Additional information
Pre-requisite abilities/skills: Dedication, Initiative, self-sufficiency, and previous experience with C++/python programming language
Maximum number of students: 2
Financial support/scholarship: Nessuno