Phd Position F/m Quantitative Analysis of X-ray
il y a 3 semaines
Le descriptif de l’offre ci-dessous est en Anglais_
**Type de contrat **:CDD
**Niveau de diplôme exigé **:Bac + 5 ou équivalent
**Fonction **:Doctorant
**Niveau d'expérience souhaité **:Jeune diplômé
**Contexte et atouts du poste**:
Ischemic stroke is a major cause of disability and death worldwide. The occlusion of blood vessels results in a potentially large area of the brain to be oxygen deprived. Recent clinical trials have demonstrated Endovascular Thrombectomy (EVT) to be highly effective, which has led to its widespread adoption in clinical routine. In the vast majority of cases, EVT is successful in the sense that recanalization is observed : the blood flow is restored in the previously blocked blood vessels, which can be assessed using Digital Subtracted Angiography (DSA). However, even when treatment has been performed within the recommended 3 hour-window after stroke onset, it is estimated that about 50% of successful recanalizations do not result in a restored perfusion in the downstream brain tissues. This phenomenon is known as _no-reflow_. But the reperfusion status cannot be readily assessed in DSA images, requiring a clinical evaluation of the outcome. Trustful quantitative tools are missing to assess the level of reperfusion after EVT, better predict potential difficulties for this reperfusion to be restored for a patient, and help the medical community better understand the underlying mechanisms of successful reperfusion. The objective of this project is to leverage recent deep learning models to develop image analysis tools and design appropriate image-based metrics to enable an immediate assessement of reperfusion based on DSA images acquired before, during and after EVT.
The Tangram Inria team has had a long standing collaboration centered on interventional imaging and simulation with medical practitioners from the Interventional Neuroradiology department of Nancy University Hospital, one of the world leaders in interventional neuroradiology. IADI Inserm team also collaborates with this medical team on developing innovative MRI imaging and multimodal image processing. This project is part of new research collaboration involving all three teams, with the aim to better understand the no-reflow phenomenon and make progress towards a more personalized, more efficient treatment for ischemic stroke. This thesis will be co-supervised by Erwan Kerrien, from Tangram team, and Julien Oster, from IADI. The PhD student will have an easy access to the medical expertise of Prof. Benjamin Gory, and colleagues.
**Mission confiée**:
DSA images present as 2D sequences of projection images showing a contrast medium flow throughout the brain vasculature to highlight the blood path. It follows three phases : arterial supply, parenchymal where the brain tissue is perfused, and the venous drainage.
The first objective will aim at automatically separating these phases. Previous works have addressed this question using Long Short Term Memory or Gated Recurrent Unit neural networks used to segment scenes in videos in a supervised way [Su21,Mittmann22], or using unsupervised Independent Component Analysis [Haouchine21,Baur24]. These fundamentally lead to uncertain solutions since they classify whole frames, whereas, due to projection and different separating times in different parts of the brain, images where phases are mixed should be considered. Unsupervised generation of three separate phase sequences will be targeted.
The third objective will target the assessment of the collateral circulation of a patient. The extension of such circulation is considered to be an important predictor of the clinical outcome, but there is currently no efficient and robust way to evaluate it [Consoli23]. Here again a multimodal approach, combining MRI and DSA imaging will be pursued.
- [Baur24] Baur, K, _et al._ (2024). "Spatiotemporal Disentanglement of Arteriovenous Malformations in Digital Subtraction Angiography." _arXiv preprint arXiv:2402.09636_.
- [van’t Hof98] van't Hof, AW _et al._ (1998). "Angiographic assessment of myocardial reperfusion in patients treated with primary angioplasty for acute myocardial infarction: myocardial blush grade". Zwolle Myocardial Infarction Study Group. Circulation. 97:2302-6.
**Principales activités**:
**Compétences**:
The applicant should hold a Master's degree (or equivalent, e.g. Engineering degree) in computer vision, data science, computer science or applied mathematics.
Fluency in English, or fluency in French with excellent level in English are mandatory to fill the position.
Software development will primarily be realized in python using PyTorch. A solid practical experience in these language and framework is expected.
**Avantages**:
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, m
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