Acquisition of a priori Information from Groupwise Registration of Inter-Patient Prostate Boundaries in MR

Registration is a complex computer vision issue that can be simplified with the aid of prior knowledge. In this paper we present the application of the groupwise method known as congealing with prostate boundaries to derive a series of transforms that can be applied to other foci for registration. Congealing provides us with transformation vectors for each image that we apply to known tumour boundaries in order to obtain a probability distribution for use as prior knowledge in future work. In this way we are able to visualise tumour locations on an mean prostate representation and provide a ‘cancer prior’ for future prostate work. The results of our initial experiment demonstrate a reliable set of affine transforms for use with prostate MR.