A method for identifying and classifying glands in histological tissue image data from a tissue sample, wherein said image data comprising a set of pixels, said method comprising the step of: - capturing (301/401) of histological tissue image data from a tissue sample that has been stained with at least one stain, wherein said at least one stain being light absorbent, and said at least one stain being absorbed primarily by the stroma; - segmenting into at least one gland, wherein a gland is surrounded by stromal tissue; - classifying said at least one gland into a category; the method is characterized by : - deriving (302/402) at least one stromal density map, wherein said at least one stromal density map corresponding to the portion of the histological tissue image data that represents the stroma and wherein said at least one stromal density map is derived using a blind color decomposition method; - wherein segmenting is done for the at least one stromal density map by: - identifying a mask, wherein said mask covering low-density regions in said at least one stromal density map, that is said mask covering non-stromal tissue, utilizing said at least one stromal density map and a contrast between the stromal tissue and non-stromal tissue in said stromal density map; - finding one seed for each disconnected or weakly connected region in said mask, said seeds being contained in said regions; - growing said seeds until said seeds meet said mask; - utilizing the boundaries of said grown seeds to identify at least one gland in the histological tissue image data. - capturing (301/401) of histological tissue image data from a tissue sample that has been stained with at least one stain, wherein said at least one stain being light absorbent, and said at least one stain being absorbed primarily by the stroma; - segmenting into at least one gland, wherein a gland is surrounded by stromal tissue; - classifying said at least one gland into a category; - deriving (302/402) at least one stromal density map, wherein said at least one stromal density map corresponding to the portion of the histological tissue image data that represents the stroma and wherein said at least one stromal density map is derived using a blind color decomposition method; - wherein segmenting is done for the at least one stromal density map by: - identifying a mask, wherein said mask covering low-density regions in said at least one stromal density map, that is said mask covering non-stromal tissue, utilizing said at least one stromal density map and a contrast between the stromal tissue and non-stromal tissue in said stromal density map; - finding one seed for each disconnected or weakly connected region in said mask, said seeds being contained in said regions; - growing said seeds until said seeds meet said mask; - utilizing the boundaries of said grown seeds to identify at least one gland in the histological tissue image data. - identifying a mask, wherein said mask covering low-density regions in said at least one stromal density map, that is said mask covering non-stromal tissue, utilizing said at least one stromal density map and a contrast between the stromal tissue and non-stromal tissue in said stromal density map; - finding one seed for each disconnected or weakly connected region in said mask, said seeds being contained in said regions; - growing said seeds until said seeds meet said mask; - utilizing the boundaries of said grown seeds to identify at least one gland in the histological tissue image data. <EOS>