Abstract: Disclosed herein is a method of generating augmented images of tissue of a patient, wherein each augmented image associates at least one tissue parameter with a region or pixel of the image of the tissue, said method comprising the following steps: obtaining one or more multispectral images of said tissue, and applying a machine learning based regressor or classifier, or an out of distribution (OoD) detection algorithm for determining information about the closeness of the multispectral image or parts of said multispectral image to a given training data set, or a change detection algorithm to at least a part of said one or more multispectral images, or an image derived from said multispectral image, or to a time sequence of multispectral images, parts of multiple images or images derived therefrom, to thereby derive one or more tissue parameters associated with image regions or pixels of the corresponding multispectral image.

Abstract: Disclosed herein is a method of generating augmented images of tissue of a patient undergoing open treatment, in particular open surgery, wherein each augmented image associates at least one tissue parameter with a region or pixel of the image of the tissue, said method comprising the following steps: estimating a spectral composition of light illuminating a region of interest of the tissue, obtaining one or more multispectral images of the region of interest, applying a machine learning based regressor or classifier to the one or more multispectral images, or an image derived from said multispectral image, to thereby derive one or more tissue parameters associated with image regions or pixels of the corresponding multispectral image, wherein said regressor or classifier has been trained to predict the one or more tissue parameters from a multispectral image under a given spectral composition of illumination, wherein the regressor or classifier employed is made to match the estimated spectral composition of l

Abstract: A method and a system for anatomical site relocalisation using dual data synchronisation. Method for repositioning, possibly several times, at a specific location, which has been already explored during a first or “reference exploration”, a flexible endoscope during one or more successive endoluminal or extraluminal subsequent or “new exploration”, or similar procedures, wherein the repositioning is realized either manually, by a human user, or automatically, by a robotic system, from or by way of a synchronisation process between a “new exploration” flexible endoscope video and the “reference exploration” flexible endoscope video displayed in parallel on or in two different windows, on one or more screens.

Abstract: A method and a system for anatomical site relocalisation using dual data synchronisation. Method for repositioning, possibly several times, at a specific location, which has been already explored during a first or “reference exploration”, a flexible endoscope during one or more successive endoluminal or extraluminal subsequent or “new exploration”, or similar procedures, wherein the repositioning is realized either manually, by a human user, or automatically, by a robotic system, from or by way of a synchronisation process between a “new exploration” flexible endoscope video and the “reference exploration” flexible endoscope video displayed in parallel on or in two different windows, on one or more screens.