Precision Segmentation Rendering for 3-D Coronary Angiography Medical Image

The 3-D coronary angiography is a useful method for physicians to diagnose heart artery stenosis. So the precision of 2-D coronary angiography image quality is very important. In this study, we present a precision 2-D image processing method that combines gradient segmentation and region segmentation approaches with an entropy maximization procedure. This method allows us to utilize all available information to achieve the most robust segmentation results for 3-D image renderings. The aim is to find a precise 3-D image processing method to handle the poor of medical image quality. The example of coronary angiography data of true medical images were used to test the validity of our method. We found our method not only achieved the precision we sought but also has many interesting applications that shall be most useful in medical practices.