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Deep Learning based medical image synthesis

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Philips

28d ago

  • Internship
    Full-time
    Summer Internship
  • Research & Development
    IT & Cybersecurity
  • Paris
  • Quick Apply

AI generated summary

  • You should have a Master's in machine learning, strong stats and deep learning knowledge, Python/PyTorch experience, and fluent English communication skills. Teamwork is essential.
  • You will compare fine-tuning methods for SAM on X-ray data, explore different prompts for segmentation tasks, and study SAM2 for processing X-ray video sequences.

Requirements

  • Troisième année d'école d'ingénieur / Master 2 Recherche, avec spécialité en apprentissage automatique, traitement d'images ou mathématiques appliquées
  • Solides connaissances en statistiques, apprentissage automatique, deep-learning et/ou traitement d'images
  • Expérience en Python et dans l’utilisation de Pytorch.
  • La maîtrise de l'anglais à l'oral, à l'écrit et en lecture est obligatoire
  • Bonne communication et capacité à travailler en équipe

Responsibilities

  • L'objectif de ce stage est d'étudier comment SAM peut être utilisé dans le contexte de la segmentation des artères coronaires et des cathéters dans des images à rayons X interventionnelles.
  • Tout d'abord, le stagiaire comparera les méthodes de fine-tuning de SAM sur des données de rayons X, en s'appuyant sur la littérature déjà importante sur le sujet.
  • Ensuite, il étudiera comment différents types de prompts pourront être utilisés pour différents types de tâches : des scribbles pour la segmentation interactive, du texte pour la segmentation sémantique des vaisseaux ou la segmentation d'instances des cathéters.
  • Enfin, comme les séquences de rayons X sont des vidéos, l'utilisation de SAM2, qui améliore SAM en permettant le traitement de données vidéo, pourra être étudiée.

FAQs

What is the main focus of the internship position?

The main focus of the internship is to study how the Segment Anything Model (SAM) can be utilized in the segmentation of coronary arteries and catheters in interventional X-ray images.

What qualifications are needed for candidates applying for this internship?

Candidates should be in their third year of engineering school or pursuing a Master 2 Research, with a specialization in machine learning, image processing, or applied mathematics.

What technical skills are required for this role?

Required skills include solid knowledge of statistics, machine learning, deep learning, and/or image processing, as well as experience in Python and using PyTorch.

Is proficiency in English necessary for this position?

Yes, proficiency in English, both spoken and written, is mandatory.

What types of tasks will the intern be involved in?

The intern will compare fine-tuning methods of SAM on X-ray data, explore different prompting techniques for various segmentation tasks, and potentially study the use of SAM2 for video data processing.

What is the significance of adapting SAM to medical images?

Adapting SAM to medical images is significant due to the sensitivity and rarity of medical data, and the costly nature of annotation, which often requires medical expertise.

What kind of team environment can the intern expect?

The intern can expect a collaborative team environment that emphasizes good communication and teamwork.

What are the potential outcomes from this internship?

Potential outcomes include developing effective techniques for medical image segmentation, gaining hands-on experience with deep learning models, and contributing to advancements in medical imaging technology.

Is there a specific application area for the research conducted during the internship?

Yes, the specific application area is the segmentation of coronary arteries and catheters in interventional X-ray images.

Are there opportunities for further career development at Philips after this internship?

Yes, there may be opportunities for further career development at Philips as they value talent and commitment to innovation within the healthcare field.

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Science & Healthcare
Industry
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Founded Year

Mission & Purpose

Philips is a global technology company that focuses on healthcare, consumer lifestyle, and lighting solutions. They are dedicated to improving people's lives through meaningful innovation and advanced technologies. Their ultimate mission is to make the world healthier and more sustainable by providing innovative healthcare solutions that enhance patient outcomes and enable better living. Additionally, Philips aims to enhance people's daily lives with their consumer products, ranging from home appliances to personal care items. Through their lighting solutions, they strive to create efficient and sustainable lighting experiences for individuals and communities, promoting energy conservation and environmental responsibility.