A computer-implemented process for classifying pixels of a digital image of a biological sample and comprising the steps of: (a) receiving a first digital image representing the biological sample , in order to obtain a value X 1 associated with each pixel of the first digital image , and obtaining at least one other value X i for each pixels from the first digital image and/or from a further digital image , i being an integer such that 2 ≤ i ≤ n and n being an integer such than n ≥ 2 ; (b) changing of space with the matrix multiplication I = A x X to obtain a second digital image , X being a matrix of n lines and 1 column including the values X 1 to X n , I being a matrix of m lines and 1 column including values I 1 to I m , m being an integer equal to 2 or higher, I 1 to I m being values associated with each pixel of the second digital image , A being a matrix of m lines and n columns; (c) determining a classification condition based on the values in I 1 and on the values in I j of at least some pixels in the second digital image with j > 1 and j ≤ m; and (d) classifying pixels of the second digital image that fulfill the classification condition in a first class ; wherein step (c) comprises: • determining a set of one or several distribution(s), the set comprising at least one distribution of a number of pixels in the second digital image as function of I 1 and the set comprising at least one distribution of a number of pixels in the second digital image as function of I j with j > 1 and j ≤ m, • fitting the distribution(s) of the set to determine at least one fitting parameter , and • determining the classification condition from the at least one fitting parameter . (a) receiving a first digital image representing the biological sample , in order to obtain a value X 1 associated with each pixel of the first digital image , and obtaining at least one other value X i for each pixels from the first digital image and/or from a further digital image , i being an integer such that 2 ≤ i ≤ n and n being an integer such than n ≥ 2 ; (b) changing of space with the matrix multiplication I = A x X to obtain a second digital image , X being a matrix of n lines and 1 column including the values X 1 to X n , I being a matrix of m lines and 1 column including values I 1 to I m , m being an integer equal to 2 or higher, I 1 to I m being values associated with each pixel of the second digital image , A being a matrix of m lines and n columns; (c) determining a classification condition based on the values in I 1 and on the values in I j of at least some pixels in the second digital image with j > 1 and j ≤ m; and (d) classifying pixels of the second digital image that fulfill the classification condition in a first class ; • determining a set of one or several distribution(s), the set comprising at least one distribution of a number of pixels in the second digital image as function of I 1 and the set comprising at least one distribution of a number of pixels in the second digital image as function of I j with j > 1 and j ≤ m, • fitting the distribution(s) of the set to determine at least one fitting parameter , and • determining the classification condition from the at least one fitting parameter . <EOS>