| Summary: | 碩士 === 朝陽科技大學 === 資訊管理系碩士班 === 98 === The grading of pathological biopsy is very important in prognosis and treatment planning for hepatocellular carcinoma. Nevertheless, the grading results interpreted by pathologists are very subject to interobserver and intraobserver variability. Therefore, providing a quantitative analysis by machine vision is thus necessary. However, the cells on the biopsy are not all in the some depth of focus under the microscope. Small variance of focus may cause some of cells in captured image become a blur. These cells may not be segmented from image or segmented with incorrect shape by the machine and thus affect the grading results. Consequently, an “all-in-focus image” is very useful to the HCC grading performed by the machine. In this paper, we proposed an image fusion approach based on the wavelet-based focus measure to fuse two images with different depth of focus into one image, which contains much more in-depth focus cells. In our experiments, we demonstrated that the fused images not only provide clear appearance of cells but also higher accuracy of grading than original images.
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