Student
Directeur.e(s) de recherche
Philippe Després
Start date
Title of the research project
Conversion of HDF5 Segmentation Files to DICOM
Description

The intern developed a tool for converting pulmonary nodule annotation data stored inHDF5 files to theDICOMfile format. The tool enables the extraction of annotation data from the HDF5 file as well as the lung computed tomography (CT) data of patients stored in a database. Subsequently, the tool generates and saves a DICOM annotation file following the structure indicated by the DICOM Standard Browser. The student programmed this tool in Python while keeping track of versions using Gitlab. The intern’s project facilitated the conversion of data for around a hundred patients.

Ultimately, the tool can be reused by other members of the research group in the future for projects requiring annotation data conversion to DICOM

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Intraoperative analgesic treatment decisions based on the NOL index: contribution of a data-based approach to improve accuracy and relevance

Student member : Marzieh Ghiyasinasab

This research project is based on the analysis of massive data on the NOL index and other intraoperative clinical parameters used by anesthesiologists during surgery. These parameters help them make analgesic treatment decisions in a non-communicating patient under general anesthesia and in whom it is impossible to assess pain and analgesic needs by standard questionnaires performed on awake patients. 
First, the objective is to interpret the values of this index in relation to the decisions made by the clinician. 

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