| Summary: | 碩士 === 逢甲大學 === 產業研發碩士班 === 104 === Medical images diagnosis is extremely important in the pathological diagnosis, such as determine cancer, osteoporosis, cerebral hemorrhage, fetal prosecutorial and guide direction of surgery, etc.. Most of the medical imaging equipments generate grayscale images, due to the limited performance of the instruments, the contrast of medical imaging equipment is usually not clear enough. because of the brightness (grayscale) is too close. The previous study designed contrast enhanced technology named PAVHE (Part Adaptively the Value of Histogram Equalization) for the contrast enhancement of medical images.
Medical personnel can point out a interested point in medical image, then an algorithm is used to automatically figure out the gray level range of the object be pointed. Finally, the special designed enhancement method will stretch the gray scale of the object for observation. Experiments show that PAVHE can not only provide excellent contrast enhanced but also zero distortion.
In this thesis, PAVHE will be implemented with hardware. By implementing PAVHE into the hardware platform to support fast processing for continuous medical video images. The proposed implementations are divided into two versions, one of the version named "A" version is designed by using FPGA (Field Programmable Gate Array) cooperated with a CPU to accomplish. a complete function of PAVHE Due to the higher cost of CPU and peripheral circuits, the thesis also developed a "B" version. Version B by simplifying the algorithm to eliminate the requirement of CPU. The version can not only greatly reduce implementation cost, but also ease the operations. According to the simulation results, we can find the version B can maintain excellent image contrast enhancement to fit the demand of marketing.
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