In cancer research, early detection and surgical treatment of tumors allow to improve the survival rate of patients. However, surgical interventions remain a complex procedure that could be highly improved by the development of computer-assisted surgery. Such an improvement can be summarized in four major steps:
- The first one consists in automated 3D modelling of patients from their medical images.
- The second one consists in using this modelling in surgical planning and simulation software, offering then the opportunity to train the surgical gesture before carrying it out.
- The third step consists in intraoperatively superimposing preoperative data onto the real view of patients. This Augmented Reality provides surgeons a view in transparency of their patient allowing to track instruments and improve pathology targeting.
- The last one consists in robotizing the procedure by replacing human gesture with robotic gesture that can be automatized (AVR team of iCube).
Liver segmentation – 3D-ircadb-01
This first database (3D-IRCADb-01) is composed of the CT-scans of 10 women and 10 men with hepatic tumours in 75% of cases. Where appropriate, the Couinaud segment number corresponding to the location of tumours is also provided.
Access to base 3d-ircadb-01
Respiratory cycle 3D-ircadb-02
This second database (3D-IRCADb-02) is composed of 2 anonymized CT-scans. The first one has been realized during the arterial phase in inhaled position, whereas the second one has been realized during the portal phase in exhaled position. The patient has a hepatic focal nodular hyperplasia in segment VII according to Couinaud’s description.
Access to base 3d-ircadb-02
Prof. Luc SOLER – Scientific Director
Dr. Alexandre HOSTETTLER – Research and Development Director
Flavien BRIDAULT – Development Director
Toby COLLINS – Research Director
Pamela LHOTE – R&D Assistant
R&D Computer Science
5 apprentices in work-study programs for a period of 3 years
1 student pursuing an engineering degree for a 6-month training end-of-course internship