Clément Mirabel

Medical Imaging R&D Engineer @ MinMaxMedical

Experience

R&D Engineer

MinMaxMedical (Grenoble, France)

Developing innovative solutions to ease surgical procedure, minimize invasiveness and increase quality of life in the field of orthopaedic surgeries. Using image processing, image analysis, machine learning, augmented reality and software development skills combined to clinical knowledge and hands-on work on anatomical parts to create solutions for the future.

August 2020 - Present

Research Assistant

Brigham and Women's Hospital (Boston, MA, USA)

Developing a surgical planning software to improve decision making for laser ablation of deep brain tumors.

March 2019 - February 2020

Master thesis

InsoleFit (Herblay, France)

Design of a 3D modeling software to design customized insoles from a surface model of patient foot. This surface is the 3D reconstruction of a cloud points generated from a set of laser images taken by a 3D scanner dedicated to podiatry.

March 2018 - September 2018

Research Assistant

University of Michigan (Ann Arbor, MI, USA)

Designed and developed a tool to dynamically interact from 3D visualization software to a database on a webserver. Presented posters and gave a workshop at researcher conventions, published a paper in a journal and attended an open source hackathon.

July 2016 - June 2017

Education

Université Claude Bernard Lyon 1 (France)

Master of Science
Image Development and 3D Technologies

Specialization: Research in Graphic Computing and Imaging

September 2017 - August 2018

Ecole supérieur de Chimie, Physique et Electronique de Lyon (France)

Master of Science - Bachelor of Science
Master in Computer Graphics - Bachelor in Digital Sciences

Majors: Image processing, signal processing, programming, databases, networking, electronics and embedded systems.

Minors: Computer graphics and artistic design. Big Data.

September 2014 - September 2018

Classes préparatoires associées CPE Lyon - Insitution des Chartreux (France)

Prep School
September 2012 - September 2014

Skills

Programming Languages & Tools

Publications

Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis

Journal of Dental Research
This study’s objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial intelligence to test shape analysis features in a neural network (NN) to stage condylar morphology in temporomandibular joint osteoarthritis (TMJOA).
Contributor - Article - July 2019

A web-based system for neural network based classification in temporomandibular joint osteoarthritis

Computerized Medical Imaging and Graphics
The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA).
Co-Author - Article - May 2018

SVA: Shape variation analyzer

Proceedings of SPIE - The International Society for Optical Engineering
Temporo-mandibular osteo arthritis (TMJ OA) is characterized by progressive cartilage degradation and subchondral bone remodeling. The causes of this pathology remain unclear. Current research efforts are concentrated in finding new biomarkers that will help us understand disease progression and ultimately improve the treatment of the disease. In this work, we present Shape Variation Analyzer (SVA), the goal is to develop a noninvasive technique to provide information about shape changes in TMJ OA.
Contributor - Conference Paper - March 2018

Languages

French

Native

English

C1 Level - Certificate in Advanced English (Cambridge English) - Overall Score 187

Spanish

Fluent

Interests