Vacancy

PhD position: Computer vision and augmented reality applied to laparoscopic liver surgery guidance
Location: Clermont-Ferrand, France
Host institutions: Institut Pascal and the city hospitals of Clermont-Ferrand and Saint-Etienne
Starting Date: when student found
Funding Duration: 3 years
Supervisors: Dr. Erol Ozgur, Dr. Mohammad Alkhatib, Prof. Adrien Bartoli, Prof. Youcef Mezouar.
Application Deadline: Open until filled

Project: This position will be funded by IMMORTALLS, an ANR-JCJC project.
Context: Liver cancer is a leading cause of cancer death worldwide. An estimated 830,000 people around the world died from the disease in 2020.
Liver resection is considered as one of the most effective treatments.
In this respect, laparoscopic liver resection (LLR) comes up by reducing substantially patient trauma compared to open liver resection.
The patient recovers faster which in return reduces healthcare costs.
However the use of LLR remains limited. This is because of three challenges.
First, controlling intraoperative bleeding using laparoscopic instruments requires advanced technical skills.
Second, the surgeon cannot manually palpate the liver and thus cannot locate the tumours and their resection margins easily.
Consequently this raises a risk of inadequate resection on the patient’s liver such as the removal of too much healthy tissue and the leaving of some cancerogenous tissue behind.
Third, laparoscopic ultrasonography (LUS), the only tool for intraoperative subsurface imaging which allows real-time tumour localisation, has a long learning curve.
This is because its design consists of a small transducer with a small field of view attached to the end of a long shaft with a pivoting mechanism.

In order to ease LLR, augmented reality (AR) based methods relying on preoperative data were proposed [1,2].
These AR-based methods predict the location of the tumours by overlaying the preoperative data onto the laparoscopy image.
These methods require the whole liver to be visible as much as possible in the laparoscopy image to make a reliable prediction.
However, the liver is usually very partially visible (i.e., about 30% or less).
Although these methods are useful to guide surgeons at the very beginning of surgery, they are neither real-time nor automatic.

[1] “Combining Visual Cues with Interactions for 3D-2D Registration in Liver Laparoscopy”, Annals of Biomedical Engineering, 2020.
[2] “Augmented Reality Guidance in Laparoscopic Hepatectomy with Deformable Semi-automatic Computed Tomography Alignment”, Journal of Visceral Surgery, 2019.

Links:
http://igt.ip.uca.fr/~ab/
https://erol-papers.github.io

Research:
We are looking for one highly motivated PhD student to study on multimodal liver tumour registrations and augmentations
to be able to guide the surgeons during LLR. The PhD student will focus on two open problems.

1/ Automatic and real-time deformable registration of a preoperative CT volume to
an intraoperative LUS image without any additional tracker sensor.
2/ Augmentation of the subsurface liver tumours and veins in the laparoscopy images
(i.e., occluded object visualisation) on a flat screen with the relevant depth cues
such that their depth can be conveyed to the surgeon accurately.

The successful outcome of the PhD will simplify mini-invasive liver surgery.
It will shorten hospital stays, improve surgical safety and accuracy, and contribute to
an overall better quality of patient life and reduction of healthcare costs.

Requirements:
1/ undergraduate and graduate degrees on Computer Science or closely related fields;
2/ excellent programming skills in C++ and python;
3/ strong theoretical and applied background in computer vision and machine learning;
4/ experience in augmented reality;
5/ proficiency in written and spoken English language.

Application:
Applicants must submit
1/ a one-page cover letter,
2/ curriculum vitae with publications list and contacts of 2 references,
3/ a copy of academic transcripts (bachelor/master grades),
4/ availability (the earliest possible starting date).

Applicants must be prepared to provide two reference letters upon request.
Once we receive your application and it fits well to the position, you will be contacted within two weeks.

Applications should be sent, *in a single PDF document*, with the email subject [IMMORTALLS PhD application] to:
erol.ozgur@sigma-clermont.fr; mohammad.alkhatib@sigma-clermont.fr; adrien.bartoli@gmail.com; youcef.mezouar@sigma-clermont.fr