Patent ID: 8483454

Claim:
A rule-based unsupervised process for classifying cervical tissue into a diagnostic class, comprising: collecting at least two digital color images of a patient cervix, one image of the patient cervix before the application of acetic acid to cervical tissue, and one image of the patient cervix after the application of acetic acid to cervical tissue; determining, based on the collected digital color images, variables for a cervical tissue classification procedure, the variables including: the size of the texture region, an opacity parameter, the size of acetowhite regions, the size of acetowhite region near os region, the size of coarse mosaics, the size of fine mosaics, the number of coarse punctations, the number of fine punctations, and the size of atypical vessels, wherein the opacity parameter is expressed by the following formula: Opacity = 1 ( 2 n - 1 ) ⁢ Ω [ ∑ i , j ⁢ ( f k * ⁡ ( i , j ) - g k ⁡ ( i , j ) ) p * r ⁡ ( i , j ) ] 1 p , where n is the number of bits of the image, f* k is the registered pre-acetic acid image and g k is the post-acetic acid image both at k band (k=1, 2, 3), r is the most opaque region extracted from the clustering algorithm in binary form, Ω is the number of foreground pixels in the opaque region r, and p is the norm metric; serially applying, using a computer, a set of classifier rules to said cervical tissue, based on the determined variables, according to a diagnosis scheme, the classifier rules including: determining the size of a texture region relative to the area of the cervix, determining an opacity parameter relative to one or more thresholds, and optionally including one or more classifier rules selected from the group consisting of: determining the size of acetowhite regions relative to area of the cervix, determining the size of acetowhite regions near os region relative to area of the cervix, determining the number of coarse and fine punctations, determining the size of coarse and fine mosaics relative to area of the cervix, and determining the size of atypical blood vessels relative to a threshold; and obtaining, based on the serial application of classifier rules according to the diagnosis scheme, a patient diagnosis classification of no evidence of disease (NED), low-grade dysplasia, high-grade dysplasia, or cancer.