Abstract

Gel dosimetry is a promising technique for the implementation of 3D dose verification within the radiation therapy clinic, since it is the only methodology which provides comprehensive 3D dose measurement of conformal treatments such as Intensity Modulated Radiation Therapy (IMRT), Stereotactic radiosurgery (SRS) and Stereotactic Radiotherapy (SRT), and volumetric arc therapies (VMAT). In polymer gel dosimetry, monomer molecules polymerize and are fixed in the gel matrix when exposed to radiation. The spatial dose information thus can be obtained by gel imaging. Gel imaging methods which are currently under investigation are MRI, optical computed tomography and x-ray computed tomography. While promising, x-ray CT images of irradiated polymer gel exhibit low contrast due to small change in density that occurs during polymerization. The response of CT contrast to dose is weak and noise reduction is critical in order to achieve adequate dose resolution in gel dosimetry using x-ray computed tomography. Ideally, image noise is minimized using high tube current, long scan times and high number of image averages [Hilts et al 2005]. Digital image filtering is an effective method in reducing image noise while maintaining accurate spatial dose information. Generally it is performed in either frequency domain or spatial domain. In a previous work, several spatial filters were applied to Stereotactic Radiosurgery (SRS) irradiated polymer gel image [Hilts and Duzenli 2004]. In their study it was found that the two highest performing filters were the adaptive mean (Wiener) and smallest univalue segment assimilating nucleus (SUSAN). In another study a new method of signal to noise ratio (SNR) enhancement by 2D two-point maximum entropy regularization method (TPMEM) was investigated [Jirasek 2006]. However, a comprehensive examination of the best performing filters from these two studies has not been undertaken. Here, we test the Weiner and TPMEM digital filters on X-ray CT image of the irradiated PAGAT gel in order to reduce noise and improve dose resolution. This work builds off of previous studies and evaluates and compares the highest-performing filters from past individual works [Hilts and Duzenli 2004, Jirasek et al 2006].

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