Mr. Jiali Wang Profile

Jiali Wang

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Proceedings Article | 26 March 2008 Paper

Automated lung tumor detection and quantification for respiratory gated PET/CT images

Jiali Wang, Anthony McGoron, Juan Franquiz, Misael del Valle

Proceedings Volume 6914, 69144G (2008) https://doi.org/10.1117/12.772862

KEYWORDS: Tumors, Positron emission tomography, Lung, Image segmentation, Image registration, Computed tomography, Algorithm development, Optical spheres, Computer simulations, Image processing

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Purpose: To develop and validate an automatic algorithm for the detection and functional assessment of lung tumors on three-dimensional respiratory gated PET/CT images. Method and Materials: First the algorithm will automatically segment lung regions in CT images, then identify and localize focal increases of activity in lung regions of PET images at each gated bin. Once the tumor voxels have been determined, an integration algorithm will include all the tumor counts collected at different bins within the respiratory cycle into one reference bin. Then the total activity (Bq), concentration (Bq/ml), functional volume (ml) and standard uptake values (SUV) are calculated for each tumor on PET images. Validation of the automatic algorithm was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System at Baptist Hospital of Miami. Tumor variables to be controlled were: volume, total number of counts (activity), maximum and average number of counts. These values were the gold standard to which the results of the algorithm were compared. The tumor's motion was also controlled with different respiratory periods and amplitudes. Results: Validation, feasibility and robustness of the algorithm were demonstrated. With the algorithm, the best compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become faster and more precise.

Proceedings Article | 17 March 2008 Paper

Low-cost respiratory motion tracking system

Misael Del Valle, Mohammed Goryawala, James Byrne, Anthony McGoron, Juan Franquiz, Jiali Wang

Proceedings Volume 6918, 691822 (2008) https://doi.org/10.1117/12.772922

KEYWORDS: Positron emission tomography, Chest, Tumors, Transducers, Motion detection, Lung, Lung cancer, Optical tracking, Laser optics, Reflectivity

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Lung cancer is the cause of more than 150,000 deaths annually in the United States. Early and accurate detection of lung tumors with Positron Emission Tomography has enhanced lung tumor diagnosis. However, respiratory motion during the imaging period of PET results in the reduction of accuracy of detection due to blurring of the images. Chest motion can serve as a surrogate for tracking the motion of the tumor. For tracking chest motion, an optical laser system was designed which tracks the motion of a patterned card placed on the chest by illuminating the pattern with two structured light sources, generating 8 positional markers. The position of markers is used to determine the vertical, translational, and rotational motion of the card. Information from the markers is used to decide whether the patient's breath is abnormal compared to their normal breathing pattern. The system is developed with an inexpensive web-camera and two low-cost laser pointers. The experiments were carried out using a dynamic phantom developed in-house, to simulate chest movement with different amplitudes and breathing periods. Motion of the phantom was tracked by the system developed and also by a pressure transducer for comparison. The studies showed a correlation of 96.6% between the respiratory tracking waveforms by the two systems, demonstrating the capability of the system. Unlike the pressure transducer method, the new system tracks motion in 3 dimensions. The developed system also demonstrates the ability to track a sliding motion of the patient in the direction parallel to the bed and provides the potential to stop the PET scan in case of such motion.

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