A method for determining the presence or absence of a local property of a biological tissue sample, comprising: • acquiring (100, 110, 120, 130) an image of the sample; • searching the image for the presence of each feature that is contained in a pre-defined set of features, and assigning, to each feature, a corresponding pronunciation index that is a measure of how pronounced each feature is in the image or parts of it, • computing at least one discriminant value, e.g. a linear discriminant value, LD, that is a function of the weighted pronunciation indices, wherein the weight of each pronunciation index is a measure for the relevance of the corresponding feature with respect to the property, and • determining that the property is present or absent in the sample or part of it depending on whether the discriminant value exceeds a pre-defined and/or optimized threshold or not, wherein • the image is a multimodal superposition of a coherent anti-stokes Raman scattering, CARS, sub-image, a two-photon excited auto fluorescence, TPEF, sub-image, and a second-harmonic generation, SHG, sub-image, with each sub-image contributing a different color to an additive mix, wherein the contribution of the sub-image to each pixel of the multimodal image has a brightness corresponding to the intensity value of this pixel in the respective sub-image, and • the property is the presence of a cell nucleus in a specific place in the sample, wherein the method further comprises: • computing the appearance of the sample that would result from exposure of said sample to at least one staining agent, preferably hematoxylin and/or eosin, as a processed version of the image, and • in response to the determining that a cell nucleus is present in a specific place, marking said cell nucleus in said specific place in the processed version of the image, wherein a pre-set partial least squares regression model, PLS, is employed in the computing of the processed version of the image by modelling the RGB values of the computationally stained image using the three color channels of the multimodal image. • acquiring (100, 110, 120, 130) an image of the sample; • searching the image for the presence of each feature that is contained in a pre-defined set of features, and assigning, to each feature, a corresponding pronunciation index that is a measure of how pronounced each feature is in the image or parts of it, • computing at least one discriminant value, e.g. a linear discriminant value, LD, that is a function of the weighted pronunciation indices, wherein the weight of each pronunciation index is a measure for the relevance of the corresponding feature with respect to the property, and • determining that the property is present or absent in the sample or part of it depending on whether the discriminant value exceeds a pre-defined and/or optimized threshold or not, wherein • the image is a multimodal superposition of a coherent anti-stokes Raman scattering, CARS, sub-image, a two-photon excited auto fluorescence, TPEF, sub-image, and a second-harmonic generation, SHG, sub-image, with each sub-image contributing a different color to an additive mix, wherein the contribution of the sub-image to each pixel of the multimodal image has a brightness corresponding to the intensity value of this pixel in the respective sub-image, and • the property is the presence of a cell nucleus in a specific place in the sample, wherein the method further comprises: • computing the appearance of the sample that would result from exposure of said sample to at least one staining agent, preferably hematoxylin and/or eosin, as a processed version of the image, and • in response to the determining that a cell nucleus is present in a specific place, marking said cell nucleus in said specific place in the processed version of the image, wherein a pre-set partial least squares regression model, PLS, is employed in the computing of the processed version of the image by modelling the RGB values of the computationally stained image using the three color channels of the multimodal image. • the image is a multimodal superposition of a coherent anti-stokes Raman scattering, CARS, sub-image, a two-photon excited auto fluorescence, TPEF, sub-image, and a second-harmonic generation, SHG, sub-image, with each sub-image contributing a different color to an additive mix, wherein the contribution of the sub-image to each pixel of the multimodal image has a brightness corresponding to the intensity value of this pixel in the respective sub-image, and • the property is the presence of a cell nucleus in a specific place in the sample, wherein the method further comprises: • computing the appearance of the sample that would result from exposure of said sample to at least one staining agent, preferably hematoxylin and/or eosin, as a processed version of the image, and • in response to the determining that a cell nucleus is present in a specific place, marking said cell nucleus in said specific place in the processed version of the image,