Fuzzy inference-based plaque boundary extraction using image separability for intravascular ultrasound image of coronary artery

A novel plaque boundary extraction method for an intravascular ultrasound (IVUS) image employing image separability and Takagi-Sugeno's fuzzy inference model is presented. The membership functions are allocated heuristically with special consideration of the features of the IVUS image. The method has not only improved the accuracy of plaque boundary extraction but has also reduced the workload of medical doctors.