Lung image segmentation and registration for quantitative image analysis

Abstract

Functional images obtained PET and/or SPECT become more useful when those images are provided with detail anatomical information obtained by X ray CT or MRI. A series of image processing including image registration and segmentation is presented for quantitative analysis of functional images. A clinical application described in the paper is to evaluate the effect of radiation therapy for lung cancer on lung functions quantitatively. Though SPECT images give information on lung functions such as ventilation and perfusion, it is difficult to identify correctly the location and amount of radioactivity distribution with only those images. To overcome this difficulty, we synthesize both anatomical image (X ray CT, or shortly XCT) and functional image (SPECT) effectively. Furthermore, we have developed a method for dividing lung in XCT image into the lobes that are anatomically meaningful. The segmented lobes in XCT image can be used for quantitative evaluation in each lobe. Change in perfusion at each lobe of lung along with the therapy is presented as an effective example.