This monograph presents a study on data mining techniques and its application in medical image analysis for cancer detection. An extensive survey and comparative study on various clustering and association mining techniques has been presented. Monograph also reported one new density based clustering technique EnDBSCAN that can detect embedded cluster structure and OPAM- an efficient one pass technique for mining frequent item sets. Results have been reported to establish the effectiveness of the works in light of various synthetic datasets. Finally it discusses about medical imaging and potentials of data mining techniques for analyzing medical imagery for detecting disease like cancer. As a case study it discusses two cancer type namely brain and skin cancer. It also proposes architecture for automatic brain cancer detection tool based on Data Mining techniques.