本文選題：高比特醫(yī)學(xué)圖像 + 圖像增強(qiáng)�。� 參考：《東北師范大學(xué)》2017年碩士論文

【摘要】：醫(yī)學(xué)成像技術(shù)已經(jīng)逐漸成為醫(yī)療診斷過程中對(duì)人體結(jié)構(gòu)進(jìn)行無損檢測的重要工具。它主要包括X射線成像、計(jì)算機(jī)斷層掃描成像(CT)、磁共振成像(MRI)、超聲成像和核醫(yī)學(xué)成像等。這幾種成像方式分別有其獨(dú)特的應(yīng)用領(lǐng)域,針對(duì)不同的生理結(jié)構(gòu)或病理情況,選用相應(yīng)的醫(yī)學(xué)成像技術(shù)。作為健康檢查和重大疾病檢測成像技術(shù)的醫(yī)學(xué)CT圖像和MRI圖像,可以展示被測人體的內(nèi)部結(jié)構(gòu)和狀態(tài),因此,圖像質(zhì)量的好壞尤為重要。DICOM是醫(yī)學(xué)圖像的國際標(biāo)準(zhǔn),被廣泛應(yīng)用于醫(yī)學(xué)成像領(lǐng)域,是一種高比特醫(yī)學(xué)圖像格式,具有信息量大,內(nèi)容豐富等特點(diǎn)。由于成像設(shè)備獲得的原始圖像受到設(shè)備本身硬件性能的制約和獲取條件等多種因素的影響,直接從醫(yī)學(xué)儀器獲得的圖像會(huì)出現(xiàn)圖像降質(zhì)現(xiàn)象,比如對(duì)比度較低、圖像模糊等。針對(duì)這一情況,本文以高比特醫(yī)學(xué)圖像作為處理對(duì)象,提出一種新的基于Laplacian金字塔和二維直方圖均衡化(2DHE)相結(jié)合的多尺度二維直方圖均衡化算法,簡稱為Lap-2DHE。在該算法中,引入Laplacian金字塔將圖像層分離,基于圖像灰度統(tǒng)計(jì)分布自適應(yīng)選取參考點(diǎn)調(diào)整塔層系數(shù),從而對(duì)圖像進(jìn)行多尺度分析,以增強(qiáng)圖像細(xì)節(jié)。再結(jié)合二維直方圖均衡化(2DHE),并采用基于模糊信噪比BSNR的方法來控制鄰域大小的選擇,使圖像增強(qiáng)達(dá)到最佳效果。本文算法有效解決了傳統(tǒng)2DHE方法在高比特醫(yī)學(xué)圖像增強(qiáng)過程中細(xì)節(jié)容易丟失的問題。實(shí)驗(yàn)結(jié)果表明,對(duì)比已有算法,Lap-2DHE算法能有效的提升對(duì)比度,增強(qiáng)圖像細(xì)節(jié),改善圖像視覺效果,對(duì)醫(yī)學(xué)圖像增強(qiáng)具有普遍適用性,對(duì)于提升無損檢測技術(shù)的實(shí)用性具有重要意義。通過圖像增強(qiáng)算法提升醫(yī)學(xué)圖像質(zhì)量,不僅提高了醫(yī)療設(shè)備實(shí)用性和可靠性,還打開了基于低劑量電磁波的成像技術(shù)應(yīng)用的局面,在醫(yī)學(xué)檢測中具有很好的應(yīng)用前景,為醫(yī)療成像設(shè)備的發(fā)展和應(yīng)用提供了可行性支持。
[Abstract]:Medical imaging technology has gradually become an important tool for nondestructive testing of human structure in the process of medical diagnosis. It mainly includes X-ray imaging, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound imaging and nuclear medicine imaging. These imaging methods have their own unique application fields, according to different physiological structure or pathological situation, the corresponding medical imaging technology is selected. Medical CT images and MRI images, as health examination and major disease imaging techniques, can display the internal structure and state of the human body under test. Therefore, the quality of images is particularly important. DICOM is the international standard of medical images. It is widely used in the field of medical imaging, is a high bit medical image format, with a large amount of information, rich content and so on. Because the original image obtained by the imaging equipment is affected by many factors such as the hardware performance of the equipment and the condition of obtaining, the image obtained directly from the medical instrument will appear the phenomenon of image degradation, such as low contrast, image blur and so on. In this paper, a new multi-scale two-dimensional histogram equalization algorithm based on Laplacian pyramid and two-dimensional histogram equalization is proposed, which is called Lap-2DHE. In this algorithm, the Laplacian pyramid is introduced to separate the image layer, and the reference point is selected to adjust the tower layer coefficient adaptively based on the image grayscale statistical distribution, so that the multi-scale analysis of the image is carried out to enhance the details of the image. Combined with two-dimensional histogram equalization and fuzzy signal-to-noise ratio (BSNR) method to control the selection of neighborhood size, the image enhancement can achieve the best results. This algorithm effectively solves the problem that the details of traditional 2DHE method are easily lost in the process of high bit medical image enhancement. The experimental results show that compared with the existing Lap-2DHE algorithm, it can effectively enhance the contrast, enhance the details of the image, improve the visual effect of the image, and have universal applicability for medical image enhancement. It is of great significance to improve the practicability of nondestructive testing technology. Improving the quality of medical image by image enhancement algorithm not only improves the practicability and reliability of medical equipment, but also opens up the application of imaging technology based on low dose electromagnetic wave, which has a good application prospect in medical detection. It provides feasibility support for the development and application of medical imaging equipment.
【學(xué)位授予單位】：東北師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R318;TP391.41

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