Technological projects portfolio

Algorithms for interpreting images to aid in early diagnosis of bladder cancer

Investment: €835k

Scope: Healthcare

Scientific field(s): Biology and medicinal chemistry / Mathematics, Information and communications science and tech. (STIC) and nanotechnology

Institution(s): Université Paris-Saclay - CNRS - ONERA - AP-HP

Development: Start-up in progress/completed

#DeepLearning #Diagnosis #BladderCancer


Bladder cancer is the 5th most common cancer in the world, and incidence is continuously increasing. The current early diagnostic techniques are not very effective, notably the non-invasive cytology techniques (search for morphological changes of cells).

Whereas detection and treatment of the cancer at an advanced stage leads to much more complicated, more costly treatments.


The FLUOALGO technology uses the analysis of urine sample images that have first been colored, to more accurately detect morphological and physiological changes.

This non-invasive test presents a higher level of sensitivity and specificity than the tests currently available.

Image processing (analysis and interpretation) is automated, which makes the test a new decision-making aid for healthcare professionals.


FLUOALGO aims to achieve early detection of bladder cancer, in combination with current cytology methods (20 million per year, worldwide), in initial diagnosis and recurrence monitoring.