[visionlist] PhD position: Computer vision and augmented reality applied to laparoscopic liver surgery guidance

Erol Ozgur erolozgur at gmail.com
Thu Aug 4 06:45:18 -04 2022

#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.
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
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] Espinel Y, Ozgur E, Calvet L, Le Roy , Buc E, Bartoli A, “Combining
Visual Cues with Interactions for
3D-2D Registration in Liver Laparoscopy”, Annals of Biomedical Engineering,
[2] Le Roy B, Ozgur E, Koo B, Buc E, Bartoli A, “Augmented Reality Guidance
in Laparoscopic
Hepatectomy with Deformable Semi-automatic Computed Tomography Alignment”,
Journal of Visceral Surgery, 2019.


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
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.

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
4/ experience in augmented reality;
5/ proficiency in written and spoken English language.

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 at sigma-clermont.fr; mohammad.alkhatib at sigma-clermont.fr;
adrien.bartoli at gmail.com; youcef.mezouar at sigma-clermont.fr;
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