Cell-Based Graph Cut for Segmentation of 2D/3D Sonographic Breast Images
Date Issued
2009
Date
2009
Author(s)
Chiang, Hsin-Hong
Abstract
In sonographic breast lesions image, circling the lesion part is the complicated and time consuming work, moreover it should be done by experienced doctors or experts. In three dimensional sonographic breast lesions image, circling the lesion part becomes more complicated and more procedure. Therefore, circling the lesion part by computer aided diagnosis(CAD) is not only simplified the circling work and saving the doctor’s precious time, but also providing more medical information by computer.egmenting the medical image by graph theory has been used and developed in couple of years. It is general used in various kinds of medical image format such that ultrasound image, X-ray, MRI and etc. In implementation, it derived lots of problem cause of enormous computation space and long computation time. Using region based method is one of solving method. Our research use Cell Competition Algorithm as producing region structure, because it has good result in ultrasound image. After producing the regions, we use Graph Cut to divide the region based graph. A good dividing approach in region based graph theory must have a good method in producing the regions and a good approach in dividing the graph, in addition to the similar weight function also plays an important role. Therefore our research designs a good similar weight function which can be used to prevent the weak edge problem and the problem of prefer cutting the isolated node in Graph Cut according the estimating statistical information of tumor. Another advantage in our research is that it can intuitively implement in three dimensional images.ast part of this paper shows the experiment result, compares with the handmade boundary and evaluates our boundary result. The experiment 2D and 3D sonographic breast lesions images are provided by National Taiwan University Hospital and Taipei Veterans General Hospital.
Subjects
Ultrasound Image
Image Segmentation
Cell Competition
Graph Cut
Region Based Graph Theory
Type
thesis
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