Our team of experts delivers innovative solutions transforming research in
biomedical imaging

Our team

Our team consists of highly skilled experts with backgrounds in biomedical research, computer science, and data analysis. We bring together these diverse areas of expertise to offer a comprehensive and tailored service that meets the specific needs of our clients. With our deep understanding of both the biological and computational aspects of image analysis and artificial intelligence, we are able to deliver innovative solutions that accelerate research and drive scientific discovery.
Victor Racine QuantaCell

Victor RACINE, PhD


Victor Racine is founder and CEO of QuantaCell. He is engineer in electronics (ISEN) and obtained a PhD from Paris 6 (France) in Biophysics at the Institut Curie. He made a postdoctoral work in Singapore (IMCB). He is more than 20-year experienced in artificial intelligence and bio-imaging. Since 2014, he is running the company.

Jocelyne Gau Racine, cofounder of QuantaCell

Jocelyne GAU, PhD


Jocelyne Gau is co-founder of QuantaCell. She is a physicist and obtained a PhD in biophysics at the University of Evry on biomolecules quantification. She is on charge of human resources.

Gaetan Galisot

Gaetan GALISOT, PhD 

Senior Data Scientist 

Gaetan Galisot specializes in the medical image segmentation and registration. He has obtained a PhD degree from Université de Tours (LIFAT). He is working on image analysis as well as on the software development.

Damien Blanc QuantaCell

Damien BLANC, PhD

Senior Data Scientist 

Damien Blanc is biostatistician. He did his PhD of mathematics at the University of Montpellier, in collaboration with the Institut Curie. He is specialized in deep learning.

Paul-Axel Marie QuantaCell

Paul-Axel MARIE, MSc

Full Stack Developer

Paul-Axel Marie is engineer in data processing (EFREI). He is full stack developer in QuantaCell. He implements graphic interfaces by combining data science and ergonomy.



Data Scientist Student

Marie Bocquelet is in the 2nd year of the IMAGINE master’s program at the University of Montpellier. During her internship, she is particularly interested in improving the learning processes of deep learning models.

Camille DOVIN, MSc

Intern in Pathology

Camille Dovin is in the 3rd year of residency in Pathology at the University Hospital of Montpellier. As part of her master’s degree, she is exploring the prognostic factors of oral cavity cancers (squamous cell carcinomas) using deep learning.

Christophe LATRILLE, PhD

Product Manager

Christophe Latrille earned a PhD in Behavioral Sciences applied to digital health at the University of Montpellier. He is interested, among other things, in the relationship between usage and tool in the product development cycle.

Our skills

Today, our team includes experts in artificial intelligence, image analysis, and statistics who work collaboratively to develop powerful software solutions that accelerate research and drive scientific discovery. With our deep understanding of both the biological and computational aspects of image analysis and artificial intelligence, we are able to guide biomedical research units towards better decision-making and improved outcomes.


Computer science

biology data analysis


biomedical imaging


machine learning

Project management

Our partners

Institut National du cancer
Brio Bordeaux
Horizon 2020

Our references with scientific publications

Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification

Nat Methods.2022 Jul;19(7):881-892. doi: 10.1038/s41592-022-01508-0. Epub 2022 Jun 13.Autors : Anne Beghin, Gianluca Grenci, Geetika Sahni, Su Guo, Harini Rajendiran, Tom Delaire, Saburnisha Binte Mohamad Raffi, Damien Blanc, Richard de Mets, Hui Ting Ong, Xareni Galindo, Anais Monet, Vidhyalakshmi Acharya, Victor Racine, Florian Levet, Remi Galland, Jean-Baptiste Sibarita, Virgile Viasnoff. Keywords : 3D imaging, Deep Learning, Quantification.

 Artificial intelligence solution to classify pulmonary nodules on CT

Diagn Interv Imaging. 2020 Dec;101(12):803-810. Autors D Blanc, V Racine, A Khalil, M Deloche, J-A Broyelle, I Hammouamri, E Sinitambirivoutin, M Fiammante, E Verdier, T Besson, A Sadate, M Lederlin, F Laurent, G Chassagnon, G Ferretti, Y Diascorn, P-Y Brillet, Lucie Cassagnes, C Caramella, A Loubet, N Abassebay, P Cuingnet, M Ohana, J Behr, A Ginzac, H Veyssiere, X Durando, I Bousaïd, N Lassau, J Brehant. Keywords : Deep learning, Retina-UNET, 3D U-Net, PyTorch
Mitochondrial morphology is associated with respiratory chain uncoupling in autism spectrum disorder

Transl Psychiatry. 2021 Oct 13;11(1):527. Autors RE Frye, L Lionnard, I Singh, MA Karim, H Chajra, M Frechet, K Kissa, V Racine, A Ammanamanchi, PJ McCarty, L Delhey, M Tippett, S Rose, A Aouacheria. Keywords : Cell segmentation, nuclei segmentation, statistics, AssayScope

Fluorescence eXclusion Measurement of volume in live cell


Methods Cell Biol. 2017. Auteurs : Cadart C, Zlotek-Zlotkiewicz E, Venkova L, Thouvenin O, Racine V, Le Berre M, Monnier S, Piel M. Keywords : Mass analysis. Biophysics, Microfluidcs

Synaptic recruitment of gephyrin regulates surface GABAA receptor dynamics for the expression of inhibitory LTP

Nature Commun. 2014 Jun 4;5:3921. PDF Auteurs Petrini EM, Ravasenga T, Hausrat TJ, Iurilli G, Olcese U, Racine V, Sibarita JB, Jacob TC, Moss SJ, Benfenati F, Medini P, Kneussel M, Barberis A. Keywords : Neuroscience, dynamique des récepteurs, suivi dans le temps, segmentation

RNAi screening reveals a large signaling network controlling the Golgi apparatus in human cells

Molecular Systems Biology. 2012;8:629PDF Auteurs Chia J, Goh G, Racine V, Ng S, Kumar P, Bard F. Keywords : Criblage phénotypique, structure cellulaire, siRNA, machine learning, statistiques

Wavelet analysis for single molecule localization microscopy

Optics Express. 2012 Jan 30;20(3):2081-95. PDF Auteurs Izeddin I, Boulanger J, Racine V, Specht CG, Kechkar A, Nair D, Triller A, Choquet D, Dahan M, Sibarita JB. Keywords : TIRF/PALM, SPT, détection moléculaire, imagerie avancée, ondelettes, fit gaussien, traitement des images

Experimental and theoretical study of mitotic spindle orientation

Nature. 2007 May 24;447(7143):493-6. Auteurs :Théry M, Jiménez-Dalmaroni A, Racine V, Bornens M, Jülicher F. Keywords : Cellule unique, détection et segmentation de compartiments, adhésion, microscopie automatisée, visualisation des données, modèle théorique, cytosquelette

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