Development of a web-based application to process and store Stimulated Raman Histology data

Development of a web-based application to process and store Stimulated Raman Histology data

Background : Histology plays a crucial role in diagnosing brain tumors, involving the extraction and analysis of a small tissue sample. The gold standard for biopsy analysis is Hematoxylin and Eosin (H&E) staining, which helps experts identify cancerous tissues but can be time-consuming [1]. An alternative, faster technique called Stimulated Raman Histology (SRH) has emerged, producing images comparable to H&E staining [2]. This technique enables to image CH₂ and CH₃ chemical bonds and channel subtraction (CH₃-CH₂) is used to highlight tissue nuclei. These images are then processed, stitched, and mapped to an H&E-like color code using virtual colorization tools [3, 4].

Missions : The candidate will have to modify and improve an existing web application that performs the corresponding processing of raw images in order to generate high quality SRH images. The main task consists of designing and building a new robust application focused only on the virtual coloring ensuring high performance and responsiveness.

Skills :

• Web application development, particularly in image analysis or related fields.
• Proficiency in front-end and back-end technologies (e.g., HTML, CSS, JavaScript, Python).
• Experience with SQL or other database management system (MongoDB)
• Experience with image processing libraries (e.g., OpenCV, Scikit-image).
• Excellent problem-solving skills and attention to detail.
• Strong communication and teamwork abilities.

Location : Institut Fresnel, 52 Av. Escadrille Normandie Niemen 13013 Marseille

Contacts : Rémi ANDRE, remi.andre@fresnel.fr – Julien WOJAK, julien.wojak@fresnel.fr; – Hervé RIGNEAULT

Candidate Profile : Student from bachelor degree to Master of Sciences in the field of Information Technology with a strong interest in web development.

Internship Duration : To define according to candidate profile

 

References
[1] Feldman, A.T., Wolfe, D. (2014). Tissue Processing and Hematoxylin and Eosin Staining. In: Day, C. (eds) Histopathology. Methods in Molecular Biology, vol 1180. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1050-2_3
[2] Barbara Sarri, Flora Poizat, Sandro Heuke, Julien Wojak, Florence Franchi, Fabrice Caillol, Marc Giovannini, and Herve Rigneault, “Stimulated Raman histology: one to one comparison with standard hematoxylin and eosin staining,” Biomed. Opt. Express 10, 5378-5384 (2019)
[3] Giacomelli MG, Husvogt L, Vardeh H, Faulkner-Jones BE, Hornegger J, Connolly JL, et al. (2016) Virtual Hematoxylin and Eosin Transillumination Microscopy Using Epi-Fluorescence Imaging. PLoS ONE 11(8): e0159337. https://doi.org/10.1371/journal.pone.0159337
[4] Romain Appay, Barbara Sarri, Sandro Heuke, Sébastien Boissonneau, Chang Liu, Etienne Dougy, Laurent Daniel, Didier Scavarda, Henry Dufour, Dominique Figarella-Branger, and Hervé Rigneault. Live Stimulated Raman Histology for the Near-Instant Assessment of Central Nervous System Samples. The Journal of Physical Chemistry B 2023 127 (16), 3624-3631 DOI: 10.1021/acs.jpcb.3c01156