| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 102 === In general, the delay from planning a course of treatment for cancer to the actual radiation therapy is over a month. In addition, the possibility of radiation therapy injuring healthy tissues will increase because the patient associates with breathing and movement in the treatment yielding the changed position of the tumor. The CT provided excellent information for spatial resolution, and doctors all use computer tomography to find tumors and to put their treatment plan into practice. In contrast, ultrasound can provide real-time information, and the capital and danger are also lower than other medical modalities. Combining spatial analysis and ultrasound to perform image registration will provide doctors with quicker and more accurate imagery and increase the effectiveness of radiation therapy.
This thesis proposed a US and CT image registration technique based on Generalized Hough Transform applying the information of edge features and further compared it to different registration methods. Since the ultrasonic image contains complex noise, the gray-scale morphology opening and anisotropic diffusion filter were used to smooth the nonuniform intensity inside some specified organs and remove the noise. Then, the target slice of CT image was extracted according to the pose of US probe in three-dimensional space. Afterwards, the edge features were extracted from both US and CT images. Finally, Generalized Hough Normalized Cross Correlation (GHNCC), Normalized Cross Correlation (NCC), Edge Normalized Correlation (ENC), Generalized Hough Transform (GHT) and Moment Invariant (MI) were used to register the position. In the experiment, all the CT and US images were captured from the phantom Model 071 produced by CIRS company to test the performance of five image registration algorithms. The registration accuracy and efficiency of the above algorithms were compared and analyzed in detail.
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