Abstract: Computer analysis of data sets representing images such as MRI images to achieve bias correction and image registration, each image including a bias in intensity within the image of unknown magnitude, is performed by: a) inputting a digital data set of a first image and a digital data set of a second image into a computer; b) calculating a deformation of said first image that transforms said first image into a transformed image that is an optimized approximation of said second image and c) simultaneously calculating and applying a bias correction which is applied to said first image and a bias correction which is applied to said transformed image such that each of the first image and the transformed image is individually corrected for bias therein. Generally, an average of the bias correction over the first image is equal and opposite to an average of the bias correction over said transformed image.

Abstract: A method of screening a population of women for breast cancer by mammography, comprising establishing a screening schedule, conducting a screening mammography on a patient in accordance with said screening schedule to obtain a mammogram image, determining whether a cancer lesion is visually observable in said mammogram image, in the event that no cancer lesion is visually observable in said mammogram image conducting a computer image analysis of the mammogram image in which no potential cancer lesion is visually observable, said method serving to determine the risk of there being such a lesion physically present or about to arise within a screening interval, said method comprising applying to the image a statistical classifier trained to score on the basis of texture features in the image that reflect such risk.