No abstract

A new inverse planning method based on the theory of variation is developed for the computation of beam intensities that produce highly conformal dose distributions to the target volume that have an arbitrary complex geometry. It is shown that the objective function defined for the optimization of external beam intensities has a unique minimum. A corresponding algorithm is then designed to generate a sequence of intensity functions that converge to the minimum. The algorithm is applied to a test geometry where the target volume has concavity and there are adjacent critical organs. The cumulative dose-area histogram, the two-dimensional version of the cumulative dose-volume histogram, is used to evaluate the outcomes of this new inverse planning method. The results show that this method creates a group of intensity-modulated external beams that produce a dose distribution consistent with the given dose prescription.

No abstract

A new algorithm has been developed to compress oncologic images using both wavelet transform and field masking methods. A compactly supported wavelet transform is used to decompose the original image into high- and low-frequency subband images. The region-of-interest (ROI) inside an image, such as an irradiated field in an electronic portal image, is identified using an image segmentation technique and is then used to generate a mask. The wavelet transform coefficients outside the mask region are then ignored so that these coefficients can be efficiently coded to minimize the image redundancy. In this study, an adaptive uniform scalar quantization method and Huffman coding with a fixed code book are employed in subsequent compression procedures. Three types of typical oncologic images are tested for compression using this new algorithm: CT, MRI, and electronic portal images with 256 x 256 matrix size and 8-bit gray levels. Peak signal-to-noise ratio (PSNR) is used to evaluate the quality of reconstructed image. Effects of masking and image quality on compression ratio are illustrated. Compression ratios obtained using wavelet transform with and without masking for the same PSNR are compared for all types of images. The addition of masking shows an increase of compression ratio by a factor of greater than 1.5. The effect of masking on the compression ratio depends on image type and anatomical site. A compression ratio of greater than 5 can be achieved for a lossless compression of various oncologic images with respect to the region inside the mask. Examples of reconstructed images with compression ratio greater than 50 are shown.

An automated field shape correlation technique based on elliptic Fourier transform (EFT) is developed to verify the radiation treatment field in digital portal images. In this method, the edge of the treatment field is initially extracted from the portal image and is then approximated by a polygon. The polygon is further represented with elliptic Fourier coefficients. The invariants to shift, rotation, and scale are computed from the elliptic Fourier coefficients to characterize the genuine shape feature and are used to match the reference treatment field. Invariants calculated from both test and reference field shapes are compared to determine the similarity between two treatment fields. The proposed procedure uses the first approved field shape as the reference for automated comparison with subsequent portal images. This technique not only verifies the shape of each portal field but also provides information about relative shift, rotation, and scale. A set of generic shapes is simulated to test the robustness of the algorithm and to determine the parameters used in the decision procedure. Experimental results on the simulated shapes show that this method can detect shape distortions of 2% in area and the standard deviations are 0 for shifting, 0.24 degrees for rotation, and 0.0031 for scaling. Preliminary tests on clinical portal images indicated that this technique is potentially useful for automated real-time portal verification.