本文關(guān)鍵詞：基于GPU的虛擬內(nèi)窺技術(shù)研究　出處：《哈爾濱工業(yè)大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 虛擬內(nèi)窺技術(shù) 中心路徑提取 三維可視化 虛擬漫游 圖形處理器

【摘要】：虛擬內(nèi)窺技術(shù)為醫(yī)療診斷開拓了新方法,它是無創(chuàng)的、非侵入式的,可以檢測(cè)極其微小的或傳統(tǒng)內(nèi)窺鏡所無法探入的器官,如腦、心臟等。雖然目前虛擬內(nèi)窺技術(shù)發(fā)展迅速,但仍存在中心路徑提取速度慢、交互效率低等問題。因此,本文的主要研究目的是將GPU的并行計(jì)算性能融入到虛擬內(nèi)窺技術(shù)的實(shí)現(xiàn)中,提高中心路徑的提取效率,開發(fā)出具備高交互性能的虛擬內(nèi)窺系統(tǒng),為臨床醫(yī)學(xué)的診療提供幫助。在中心路徑提取方面,本文采用勢(shì)能場方法。為了降低該方法的時(shí)間復(fù)雜度,提出了基于GPU的勢(shì)能場中心路徑提取并行算法,并充分利用CUDA架構(gòu)特有的常量存儲(chǔ)器和共享存儲(chǔ)器對(duì)普通并行算法進(jìn)行改進(jìn)。通過對(duì)多組3D模型進(jìn)行測(cè)試,結(jié)果表明,隨著數(shù)據(jù)規(guī)模的增大,加速效果逐漸提升。處理256×256×487的體數(shù)據(jù)時(shí),可獲得18倍的加速比,解決了中心路徑提取時(shí)間長、效率低的問題。在三維可視化方面,本文實(shí)現(xiàn)了基于移動(dòng)立方體算法的面繪制和基于光線投射算法的體繪制。由于體繪制運(yùn)算量大,僅用CPU進(jìn)行計(jì)算常常無法滿足實(shí)時(shí)繪制的要求。因此,本文還提出了基于GPU的并行體繪制方法,利用GPU的并行計(jì)算性能來提高繪制幀率。測(cè)試結(jié)果表明,對(duì)于多組不同大小的3D模型,該并行方法的繪制幀率均可達(dá)到40以上,滿足實(shí)時(shí)繪制的要求。另外,本文還提供了實(shí)時(shí)交互功能,用戶可自行設(shè)置傳遞函數(shù)以達(dá)到理想的繪制效果,并可對(duì)可視化結(jié)果進(jìn)行放縮、旋轉(zhuǎn)和拖動(dòng)等操作。在虛擬漫游方面,本文將平行投影改為透視投影以實(shí)現(xiàn)近大遠(yuǎn)小的視覺感官效果。提供引導(dǎo)式漫游方式,用戶可操控虛擬相機(jī)沿著中心路徑進(jìn)行漫游,或固定在某一位置對(duì)局部進(jìn)行細(xì)微觀察,通過點(diǎn)擊鼠標(biāo)或按鈕完成虛擬相機(jī)鏡頭的放縮或旋轉(zhuǎn)等操作。最后,本文融合了以上三項(xiàng)技術(shù),設(shè)計(jì)并實(shí)現(xiàn)了基于GPU的虛擬內(nèi)窺系統(tǒng),該系統(tǒng)具備較好的交互性能,可改善用戶體驗(yàn),為臨床醫(yī)學(xué)的診療提供有效的輔助平臺(tái)。
[Abstract]:Virtual endoscopy opens up a new method for medical diagnosis. It is noninvasive and can detect extremely small or undetectable organs such as the brain. Although virtual endoscope technology is developing rapidly at present, there are still some problems such as slow center path extraction and low interaction efficiency. The main purpose of this paper is to integrate the parallel computing performance of GPU into the implementation of virtual endoscope, improve the efficiency of central path extraction, and develop a virtual endoscope system with high interaction performance. In order to reduce the time complexity of this method, a parallel algorithm based on GPU for center path extraction of potential energy field is proposed. And make full use of the CUDA architecture unique constant memory and shared memory to improve the common parallel algorithm. Through the multi-group 3D model test, the results show that, with the increase of data size. When processing 256 脳 256 脳 487 volume data, the acceleration ratio can be obtained by 18 times, which solves the problem of long time and low efficiency of center path extraction. In this paper, surface rendering based on moving cube algorithm and volume rendering based on ray-casting algorithm are realized. Because of the large amount of volume rendering computation, only CPU can not meet the requirements of real-time rendering. This paper also proposes a parallel volume rendering method based on GPU, which uses the parallel computing performance of GPU to improve the frame rate of rendering. The test results show that, for many groups of 3D models of different sizes. The rendering frame rate of the parallel method can reach more than 40, which can meet the requirement of real-time rendering. In addition, the real-time interactive function is provided in this paper. The user can set the transfer function to achieve the ideal rendering effect. In virtual roaming, the parallel projection is changed to perspective projection to realize the visual sense effect of near, far and small. The user can control the virtual camera to roam along the central path, or fix a certain position to make a fine observation of the local area, and by clicking the mouse or button to complete the virtual camera lens zooming or rotation operations. Finally. This paper integrates the above three technologies and designs and implements a virtual endoscope system based on GPU. The system has good interaction performance and can improve the user experience and provide an effective auxiliary platform for the diagnosis and treatment of clinical medicine.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：R443;TP391.41

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前2條

1 馬雪君;基于體繪制的虛擬內(nèi)窺鏡技術(shù)研究[D];長春理工大學(xué);2010年

2 孟寧;基于VTK的三維醫(yī)學(xué)影像診斷系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[D];鄭州大學(xué);2014年

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本文編號(hào)：1436580