Localized and detailed analyses of 3D abdominal images obtained through different imaging modalities help greatly in determining the progression of a disease or for postoperative treatment / evaluation. However, such analyses become difficult and sometimes unfeasible due to the effects of patient motion and breathing. This is particularly evident during analysis of the pancreas for cancer, due to its proximity to other intra-abdominal organs. Within subject registration thus becomes imperative for pathological analysis of pancreatic cancer. An intensity-based, global image registration algorithm was developed in the present work, for registration of pancreatic abdominal images. The registration algorithm was automatic and could register three dimensional MR and CT images of the abdomen. Once registered, localization and analysis of the pancreas was facilitated by a semi-automatic k-means clustering based segmentation procedure. Such a registration and segmentation based method could be used as a valuable tool for pancreas cancer screening and analysis.