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- Application deadline: November 30th, 2018
- Beginning of the internship: February 4th, 2019
- Duration: 6 months (longer duration possible condition to an agreement with the University/School)
- Financial support: according to the competencies and the motivation of the candidate
- Locations of the internships: Lyon, France
More details in the pdf file
Keywords:
Image Classification, Medical Image Analysis, Machine Learning (ML), Deep Learning (DL),
Generative Adversarial Networks (GAN), Hidden Markov Model – HMM, Multiple Instance Learning (MIL),
Convolutional Neural Networks (CNN), U-net, Graph Theory, TensorFlow, Keras.
Project – OPERATIONAL SYSTEM FOR AUTOMATIC CEPHALOMETRIC ANALYSIS
The project consists of the construction of an efficient and effective operational system for the
recognition of anatomical points on a 2D cephalometric radio. This operation is essential for a good
preparation of an orthodontist’s work. Among the multitude of existing points, we will set the
priorities according to the importance and the discriminating aspect of the point, facilitating its
automatic detection. Supporting this first detection - which will be done using deep machine
learning - Bayesian models and graphs are to be considered to consolidate the reconstruction of
the entire layout. If performance requires it, a 3D virtual model could be built and used to make
the approach more robust.
Context of the internship:
KITVIEW develops innovative solutions based on image analysis (medical and natural) to
continuously improving the ergonomics of its software, offering advanced features to its customers
and partners, as well as targeting new markets in France and abroad.
Competencies (selection) requested to reinforce our R&D projects:
- Image Classification, Pattern recognition, Machine Learning (SVM, Random Forest, HMM ...), Deep
Learning (CNN, U-net, GAN, MIL - Libraries: TensorFlow...);
- Medical image analysis, conditional probabilities, graph theory;
- Rapid prototyping of ergonomic, modern software interfaces.
Applicant profile:
- University Master or Engineering School student (last year of study) with computer science, image
analysis and/or applied mathematics profile;
- Interest, curiosity, learning capability and creativity are qualities we do appreciate;
- Positive spirit, communication skills and ability to work in a team, if necessary;
- Autonomy, dynamism and motivation to advance his/her own part of the project;
- Excellent methodological and hands-on computer programming skills. Programming languages:
Python, C ++. Libraries: TensorFlow, Keras, Open CV, CUDA;
- Facility of understanding and manipulating mathematical models.