Team : SYEL
Arrival date : 10/01/2021
- Sorbonne Université - LIP6
Boîte courrier 169
Couloir 26-00, Étage 5, Bureau 516
4 place Jussieu
75252 PARIS CEDEX 05
Tel: +33 1 44 27 87 26, Garance.Martin (at) nulllip6.fr
Supervision : Andrea PINNA
Co-supervision : BLOCH Isabelle (LIP6) - SZEWCZYK Jérôme (ISIR)
Image analysis with artificial intelligence methods for interventional radiology
Endoscopic retrograde cholangiopancreatography or ERCP is an operation of the bile ducts, aimed at removing stones or diagnosing cancer. This operation takes place under 2D radiographic control to verify the location of surgical instruments such as catheter, guidewire etc.
The 3D anatomy of the biliary tree and the great interpatient variability make this act, however minimally invasive, very complex to perform.
The radio opacity of the instruments is not sufficient for the localization of the latter. This is why the use of contrast agent is necessary. However, this exposes the patient to complications which can prove to be serious.
The aim of this thesis is to propose reproducible and explainable artificial intelligence methods for the localization of surgical instruments in the biliary tree.
For this, we will rely in particular on the results obtained previously as well as the use of mathematical morphology for the modeling of the topology of the instruments.