11 May 1994 Clinical tool for enhancement of portal images
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Abstract
Demonstrably effective enhancement of portal films is now available to practicing radiation therapists. The combination of a straightforward user interface and an algorithm that runs in a clinically-reasonable time improves our previously-reported technique and makes it accessible to clinicians. Radiation portal images remain the most important mechanism for assuring geometric accuracy of radiation therapy delivery. The high-energy x-ray beams, however, produce films that are intrinsically of low contrast and so they can vary widely in quality, making consistent interpretation difficult. Our current work improves image quality further by adding the option for a median-filtering operation at the output of SHAHE. This step removes much of the local noise that is sometimes introduced despite the contrast- limiting step. Using a new graphical-user-interface-builder, we have built a portal image enhancement system designed to be used by the non-expert. Four levels of enhancement are available: high and low contrast, with and without the median filter. Adjustment of all seven SHAHE parameters is possible for the expert user, but is discouraged for routine use because many of the regions of 'enhancement space': have not been explored for accuracy. The user of the system is presented with a display that allows the selection of an input image and the level of enhancement. Typical computation times (for a 2048 x 2048 image) on a Sun Sparc 400 computer average approximately 10 minutes. Clinical portal imaging -- especially as digital capture is introduced -- should be able to benefit measurably from the use of the methods described here.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Murray H. Loew, Murray H. Loew, Julian G. Rosenman, Julian G. Rosenman, Jun Chen, Jun Chen, } "Clinical tool for enhancement of portal images", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); doi: 10.1117/12.175089; https://doi.org/10.1117/12.175089
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