There has been increased interest in the development of fuzzy pattern recognition based medical imaging that contributes to solve the problems in early diagnosis and prognosis. In the context of medical imaging, uncertainties can be present at any point that can lead to serious inaccuracy with segmentation. There are several complementary and competing approaches to computer aided diagnosis, including fuzzy logic, neural networks and hybrid algorithms. To extract the interested structures, many researchers aim to develop fuzzy segmentation algorithms in medical data. Many fuzzy pattern recognition approaches have shown their effectiveness in medical diagnosis. This paper surveys the algorithmic methods of fuzzy pattern recognition for medical imaging.