Segmentation of mouse dynamic PET images using a multiphase level set method
| Autor: | Jinyi Qi, Jinxiu Cheng-Liao |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Level set method
Radiological and Ultrasound Technology business.industry Computer science Phantoms Imaging Image processing Image segmentation computer.software_genre Article Weighting Mice Robustness (computer science) Voxel Fluorodeoxyglucose F18 Positron-Emission Tomography Image Processing Computer-Assisted Animals Radiology Nuclear Medicine and imaging Segmentation Computer vision Computer Simulation Artificial intelligence business computer |
| Zdroj: | Physics in medicine and biology. 55(21) |
| ISSN: | 1361-6560 |
| Popis: | Image segmentation plays an important role in medical diagnosis. Here we propose an image segmentation method for four-dimensional mouse dynamic PET images. We consider that voxels inside each organ have similar time activity curves. The use of tracer dynamic information allows us to separate regions that have similar integrated activities in a static image but with different temporal responses. We develop a multiphase level set method that utilizes both the spatial and temporal information in a dynamic PET data set. Different weighting factors are assigned to each image frame based on the noise level and activity difference among organs of interest. We used a weighted absolute difference function in the data matching term to increase the robustness of the estimate and to avoid over-partition of regions with high contrast. We validated the proposed method using computer simulated dynamic PET data, as well as real mouse data from a microPET scanner, and compared the results with those of a dynamic clustering method. The results show that the proposed method results in smoother segments with the less number of misclassified voxels. |
| Databáze: | OpenAIRE |
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