Method for processing a digital tissue sample image comprising the steps of: - Acquiring an input about a target object class to be searched within the image; - Associating a set of morphological and chromatic parameters of the target class to a pre-set initialization value range selected from a library on the basis of the input; - Processing the tissue image on the basis of the set of parameters via a first segmentation algorithm to identify objects within the target object class; - Providing a result set comprising the objects complying with parameters within the pre-set initialization value range; - Checking whether a count of objects within the result set reaches a predefined threshold and ∘ either entering an initial loop if the count is below the predefined threshold, the initial loop comprising, for each iteration, the steps of providing an initial loop value range for at least one morphological and/or chromatic parameter, the initial loop value range being broader than the pre-set initialization value range or than an initial loop value range of the previous iteration, and the step of repeating said steps of processing, providing and checking, said processing step being applied to the initial loop value range; ∘ or entering an adaptation branch comprising the steps of: ▪ generating an adapted value range for said parameters based on the objects within the result set complying with the step of checking via a feature extraction algorithm, the adapted value range being broader than the initialization value range; ▪ processing the tissue image via a second segmentation algorithm to identify objects complying with the parameters within the adapted value range to provide an adaptation loop result set; ▪ applying a similarity test to said adaptation loop result set and a set comprising the result set complying with the step of checking. - Acquiring an input about a target object class to be searched within the image; - Associating a set of morphological and chromatic parameters of the target class to a pre-set initialization value range selected from a library on the basis of the input; - Processing the tissue image on the basis of the set of parameters via a first segmentation algorithm to identify objects within the target object class; - Providing a result set comprising the objects complying with parameters within the pre-set initialization value range; - Checking whether a count of objects within the result set reaches a predefined threshold and ∘ either entering an initial loop if the count is below the predefined threshold, the initial loop comprising, for each iteration, the steps of providing an initial loop value range for at least one morphological and/or chromatic parameter, the initial loop value range being broader than the pre-set initialization value range or than an initial loop value range of the previous iteration, and the step of repeating said steps of processing, providing and checking, said processing step being applied to the initial loop value range; ∘ or entering an adaptation branch comprising the steps of: ▪ generating an adapted value range for said parameters based on the objects within the result set complying with the step of checking via a feature extraction algorithm, the adapted value range being broader than the initialization value range; ▪ processing the tissue image via a second segmentation algorithm to identify objects complying with the parameters within the adapted value range to provide an adaptation loop result set; ▪ applying a similarity test to said adaptation loop result set and a set comprising the result set complying with the step of checking. ∘ either entering an initial loop if the count is below the predefined threshold, the initial loop comprising, for each iteration, the steps of providing an initial loop value range for at least one morphological and/or chromatic parameter, the initial loop value range being broader than the pre-set initialization value range or than an initial loop value range of the previous iteration, and the step of repeating said steps of processing, providing and checking, said processing step being applied to the initial loop value range; ∘ or entering an adaptation branch comprising the steps of: ▪ generating an adapted value range for said parameters based on the objects within the result set complying with the step of checking via a feature extraction algorithm, the adapted value range being broader than the initialization value range; ▪ processing the tissue image via a second segmentation algorithm to identify objects complying with the parameters within the adapted value range to provide an adaptation loop result set; ▪ applying a similarity test to said adaptation loop result set and a set comprising the result set complying with the step of checking. ▪ generating an adapted value range for said parameters based on the objects within the result set complying with the step of checking via a feature extraction algorithm, the adapted value range being broader than the initialization value range; ▪ processing the tissue image via a second segmentation algorithm to identify objects complying with the parameters within the adapted value range to provide an adaptation loop result set; ▪ applying a similarity test to said adaptation loop result set and a set comprising the result set complying with the step of checking.