本文選題：低劑量CT圖像重建 + 有限角度投影數(shù)據(jù)��； 參考：《南京郵電大學(xué)》2017年碩士論文

【摘要】：X射線(xiàn)計(jì)算機(jī)斷層成像技術(shù)(X-ray Computerized Tomography,CT)能夠?yàn)榕R床醫(yī)生的診斷提供豐富的人體器官組織解剖信息,是臨床診斷和治療的有效工具之一。但是一次完整的CT掃描會(huì)對(duì)人體產(chǎn)生較大的電離輻射傷害,如果長(zhǎng)時(shí)間暴露在高劑量的電離輻射下容易引發(fā)癌癥等疾病。雖然減少CT投影數(shù)據(jù)能夠有效降低X射線(xiàn)劑量、減少電離輻射傷害,但是同時(shí)也會(huì)造成CT重建圖像質(zhì)量下降,從而影響臨床醫(yī)生的診斷。因此,如何在低劑量X射線(xiàn)條件下重建出符合臨床診斷要求、高質(zhì)量的二維或三維CT圖像具有重要的臨床實(shí)用價(jià)值。為了在部分平行束投影數(shù)據(jù)缺失的情況下提高二維CT重建圖像質(zhì)量,本文提出了基于Krawtchouk離散正交矩的有限角度二維C T圖像重建算法。該算法利用Krawtchouk離散正交矩和二維Radon變換的性質(zhì)建立了Krawtchouk離散正交矩和二維Radon變換之間的關(guān)系,然后通過(guò)此關(guān)系先從已知角度投影數(shù)據(jù)中獲得Krawtchouk離散正交矩,然后再通過(guò)已獲得的Krawtchouk離散正交矩來(lái)估計(jì)未知角度投影數(shù)據(jù),從而達(dá)到補(bǔ)全投影數(shù)據(jù)、提高重建圖像質(zhì)量的目的。實(shí)驗(yàn)結(jié)果表明,本文方法能夠在投影數(shù)據(jù)缺失的情況下有效提高二維重建圖像質(zhì)量。其次,為了在部分錐形束CT投影數(shù)據(jù)缺失的情況下提高三維CT重建圖像質(zhì)量,本文提出了基于幾何矩的有限角度錐形束CT圖像重建算法。該算法利用Grangeat公式將獲得的已知錐形束投影數(shù)據(jù)轉(zhuǎn)化為已知三維Radon變換數(shù)據(jù),然后建立了三維Radon變換與三維幾何圖像矩之間的關(guān)系,并通過(guò)此關(guān)系從已知三維Radon變換數(shù)據(jù)中計(jì)算出三維幾何圖像矩,再?gòu)囊勋@得的三維幾何圖像矩估計(jì)出未知三維Radon變換數(shù)據(jù),最后直接使用三維Radon逆變換重建出圖像。從實(shí)驗(yàn)結(jié)果可以看出,在部分錐形束CT投影數(shù)據(jù)缺失時(shí),該方法仍能獲得質(zhì)量較好的三維CT圖像。
[Abstract]:X-ray Computerized Tomography can provide abundant anatomical information of human organs and tissues for the diagnosis of clinicians. It is one of the effective tools for clinical diagnosis and treatment. However, a complete CT scan can cause more ionizing radiation damage to human body. If exposed to high dose of ionizing radiation for a long time, cancer and other diseases can be easily caused. Although the reduction of CT projection data can effectively reduce the dose of X-ray and reduce the injury of ionizing radiation, it will also cause the quality of CT reconstruction image to decline, thus affecting the diagnosis of clinicians. Therefore, how to reconstruct 2D or 3D CT images with high quality under the condition of low dose X-ray is of great clinical value. In order to improve the quality of 2D CT reconstruction image without some parallel beam projection data, a finite angle 2D CT image reconstruction algorithm based on Krawtchouk discrete orthogonal moments is proposed in this paper. Based on the properties of Krawtchouk discrete orthogonal moment and two-dimensional Radon transform, the relationship between Krawtchouk discrete orthogonal moment and two-dimensional Radon transform is established, and then the Krawtchouk discrete orthogonal moment is obtained from the known angle projection data. Then the unknown angle projection data are estimated by the obtained Krawtchouk discrete orthogonal moments, which can complement the total projection data and improve the image quality. The experimental results show that the proposed method can effectively improve the quality of 2D reconstructed images without projection data. Secondly, in order to improve the image quality of 3D CT reconstruction, a finite angle cone-beam CT image reconstruction algorithm based on geometric moments is proposed in this paper. In this algorithm, the known conical beam projection data are transformed into known 3D Radon transform data by Grangeat formula, and the relationship between 3D Radon transform and 3D geometric image moments is established. The moment of 3D geometric image is calculated from the known 3D Radon transform data, and then the unknown 3D Radon transform data is estimated from the obtained 3D geometric image moment. Finally, the image is reconstructed directly by using 3D Radon inverse transform. From the experimental results, it can be seen that the method can still obtain good quality 3D CT images when part of the conical beam CT projection data is missing.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R814.42;TP391.41

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本文編號(hào)：1901008