Change detection of the lung cancer using image registration and Thin-Plate Spline warping
Lung cancer has the lowest survival rate comparing to other types of cancer and determination of the patients cancer stage is the most vital issue regarding the cancer treatment process. In most cases accurate estimation of the cancer stage is not easy to achieve. The changes in the size of the primary tumor can be detected using image registration techniques. The registration method proposed in this paper uses Normalized Mutual Information metric and Thin-Plate Spline transformation function for the accurate determination of the correspondence between series of the lung cancer Computed Tomography images. The Normalized Mutual Information is used as a metric for the rigid registration of the images to better estimate the global motion of the tissues and the Thin Plate Spline is used to deform the image in a locally supported manner. The Control Points needed for the transformation are extracted semiautomatically. This new approach in change detection of the lung cancer is implemented using the Insight Toolkit. The results from implementing this method on the CT images of 8 patients provided a satisfactory quality for change detection of the lung cancer.
Image registration Landmark extraction Normalized Mutual Information Thin-Plate Spline Canny-Edge detector Lung cancer Tumor change detection medical image processing Insight Toolkit
Dawood M. S. Almasslawi Ehsanollah Kabir
Department of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
国际会议
Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)
成都
英文
164-169
2011-04-15（万方平台首次上网日期，不代表论文的发表时间）