| Cervical cancer is one kind of disease that seriously threatens the woman health, also is one of the most common malignant tumors that occupy our country woman tumor, and is the first women cancer. That combined with in-vitro exposure and after-loading radiation has been considered the standard method to heal cervical cancer for long time. It is important to forecast the side effect of radiotherapy, optimize the radiotherapy plan, and enhance the curative effect that we can accurately know the dosage distribution of all important organs and tissues for cervical cancer treated by after-loading radiation.In the first part of this article, we did the complete and intensive study about dosage distribution, determination method and operation technology for cervical cancer treated by modern after-loading radiation, then compared merits and demerits of a multitude of methods of current dosage optimization. In the near distance radiotherapy it is an important link and one difficult point to carry on dosage optimization. In majority domestic development treatment plan software, it is very few to optimize dosage distribution, or uses simple and backward methods. To solve a series of optimization equations has been the main method for people to study dosage distribution. Some traditional methods, such as singular value decomposition, parameter method, geometrical optimization, develop on this base. Reference point establishment of dose-point optimization is the critic of dosage optimization. At the same time, position of appliance, also is one of very weighty factors for dosage distribution and dosage optimization.In the clinical surveying experiment, we used the thermo luminescent dosimeter (TLD) [ LiF (Mg, Cu, p) ] and simulation pelvic human phantom to test dosage distribution for cervical cancer treated by after-loading radiation. Methods: 1.To select JR1152-F TLD components (specification: Immxlmmx6mm) to determine temperature programming in the iridium -192 dosage survey, dosage linear response range and repeatability character, and do the dosage scale for TLD component and thermo magnetic analysis machine(FJ427-Al). 2. To divide pelvic cavity of simulation human phantom into six layers, and certain testing poles (φ1mm ×6mm) are established on essential organs of each stratification, little leads (φ1mm ×6mm)are put in the hole, we insert tandem appliance, screen X-ray films under simulator, take out the leads, put the TLD components into holes, design intracavitary simulative plan by microSelectroHDR system, give point A dosage 200cGy each time, calculate the theory value and the reconstruction precision of various test points, and carry on after-loading radiation according to the plan. The TLD components irradiated are tested repeatedly by thermo magnetic analysis machine. 3 .By the unified and definite irradiation, to set stepped 34 dosimeters apart lmm on the seventeen positions from 4mm to 20mm of water tank, cover by the simulation phantom, and be irradiated by after-loading planning system in lOcGy, test five times, and measure via adopting No. 1 temperature programming of thermo magnetic analysis machine. Apart from maximum or minimum value, we worked out the average. Conclusions: The TLD components' dosage linear range is 0-300cGy; It repeat well; The testing dosage well accords with the computing dosage, average error is ±5.16%; In more approaches the radioactive source the place, the bigger errors of dosage exists between the near source area and the TPS value, but it is perfectly in accord with the computation values by TPS once far away the radioactive source, that is caused by gradient. On the whole, from experiments conclusions, testing dosage can better reflect exposure dosage of patients. It is important value to forecast radiotherapy side effect, optimize radiotherapy plan, enhances curative effect.In the second part of this article, we did primary work about three dimensions modeling. We chiefly studied the technology and methods during Digital Virtual Female images were handled. For the better display of two-dimensional images, we used image inversion and image enhancement, which direct methods all is based on pixels, and the algorithm is easy to realize also the effect is better.In order to match all anatomical points on the consecutive images in the series images, or at lest the points that have a diagnostic meaning, we used two ways to accomplish image registration individually. Translation registration is to adopt pair pixels' same degrees that on the neighboring images as measurement, that is more and more same pair pixels, more and more similar is of two images, and by this to determine how to move the image, thus start the next round comparison, until obtain the most same numbers of pair pixels. This matching method is considered the high precision of colored images; its main merit is simple code designation. The other registration method is based on mutual information. When complete registration, it regards relevant is the biggest, which is weighed by mutual information. The most important in this algorithm is to work out mutual information of two images. During coordinate's transformation, integral coordinates of pixels are changed to float ones, so when we get image histogram, interpolation must be used to this points' gray. In this study, we used bilinear interpolation. There are merits such as better precision and robustness if registration that based on mutual information be compared to translation registration and ones based on characteristic. It is accepted by most of researchers. But it takes to long time to search. So far, no better way can solve local maxima oThis research is one part of such projects as Guangdong Province science and technology plan project (Serial Number: C30601): "Cervical cancer radiotherapy dosage optimization and feminine pelvic cavity model development", and GuangdongProvince natural sciences fund project (Serial Number: C37065): "Study on digital visual 3D anti-radiation human modeling and photon transportation," a part of dose optimization and reconstruction of relevant organs.
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