Vitadx International

Institut Pasteur

Centre National De La Recherche Scientifique

Océ Holdings B.v.

Riadh Fezzani

Alexandre Bouyssoux

Thibaut Troude

Cédric T Valade

Jean-Christophe Olivo-Marin

Florent Couzinie-devy

Marin Scalbert

Shuxian Li

Florent Couzinié-devy

Jean-Christophe Olivo-marin

A computer-implemented and a device for analysis of a digital cytology slide of a biological sample. The biological sample having been previously collected from a subject suspected to be suffering from bladder cancer, the device including: at least one input configured to receive at least one digital cytology slide obtained from the biological sample; at least one processor configured to: detect cells of interest from the at least one digital cytology image; for each cell of interest, compute a features vector including at least one feature calculated on each cell of interest; define a bag of k instances for each digital cytology slide; calculating a global prediction score representative of a probability of presence of bladder cancer and/or a stage of bladder cancer for the subject; at least one output configured to provide the global prediction score.

Method for identifying abnormalities in cells of interest in a biological sample

A method for classifying and counting objects recoverable from a urine sample processed onto a slide. The method includes the following steps: receiving at least one digitalized image of the whole slide; detecting connected components by segmentation of the image of the whole slide; classifying the detected connected components into countable connected components and uncountable connected components using a classifier; for the countable connected components using an object detection model to obtaining the number of objects for each class; for the uncountable components using a semantic segmentation model to obtaining the number of objects for each class; summing up the number of objects for each class obtained from the semantic segmentation model and the object detection model outputting a number of objects for each class.

Systematic characterization of objects in a biological sample

A method for generating a color-faithful extended-depth-of-field (EDF) image from a color volume of 2D images acquired at different focal depths using a microscope. The method involves: generating a grayscale volume; applying invertible color-to-grayscale transformation to the volume; applying wavelet transform to the grayscale volume to obtain a 3D wavelet-coefficient-matrix (WCM); selecting wavelet coefficients using a coefficient selection rule; generating a 2D-WCM and a 2D coefficient-map (CM); applying inverse transformation of the wavelet transform to the 2D-WCM to obtain a 2D grayscale EDF image; generating a 2D color-composite(CC) image; applying inverse transformation of the color-to-grayscale transformation to the 2D grayscale EDF image to obtain a 2D color EDF image; converting the 2D-CC image and the 2D color EDF image into a color space including chromaticity and intensity component(s); and concatenating, chromaticity component(s) of the 2D-CC image and intensity component(s) of the 2D color EDF image, to obtain a color-faithful EDF image.

Multi-channel extended depth-of-field method for automated digital cytology

A system for detecting friction between an object, that is being printed in a printer, and a print head moving relative to the object, comprising: an acoustic sensor system arranged to detect an acoustic noise signal generated by the printer; a recording system arranged to record the noise signal while the print head moves relative to the object; and an electronic processing system arranged to detect, in the recorded noise signal, correlated with the reciprocating movement of the printhead over the printed object, a signature that is characteristic of an event of friction between the print head and the object.

Print head friction detection system

Growing community of inventors

Montrouge, France

Riadh Fezzani