Alignment by Maximization of Mutual Information
International Journal of Computer Vision
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
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This paper presents a method to analyze volume evolutions of pulmonary nodules for discrimination between malignant and benign nodules. Our method consists of four steps; (1) The 3-D rigid registration of the two successive 3-D thoracic CT images, (2) the 3-D affine registration of the two successive region-of-interest (ROI) images, (3) non-rigid registration between local volumetric ROIs, and (4) analysis of the local displacement field between successive temporal images In preliminary study, the method was applied to the successive 3-D thoracic images of two pulmonary lesions including a metastasis malignant case and a inflammatory benign to quantify the evolving process in the pulmonary nodules and surrounding structure. The time intervals between successive 3-D thoracic images for the benign and malignant cases were 150 and 30 days, respectively. From the display of the displacement fields and the contrasted image by the vector field operator based on the Jacobian, it was observed that the benign case reduced in the volume and the surrounding structure was involved into the nodule in the evolution process. It was also observed that the malignant case expanded in the volume. These experimental results indicate that our method is a promising tool to quantify how the lesions evolve their volume and surrounding structures.