本文選題：醫(yī)學(xué)超聲圖像 + 分?jǐn)?shù)階微分��； 參考：《昆明理工大學(xué)》2017年碩士論文

【摘要】：因?yàn)獒t(yī)學(xué)超聲成像具有低成本、高效率、實(shí)時、方便安全的特點(diǎn),所以它已逐漸成為最重要的診斷工具之一。然而粒狀結(jié)構(gòu)疊加的斑點(diǎn)噪聲廣泛存在于醫(yī)學(xué)超聲B模式圖像中,其噪聲表現(xiàn)為像素灰度值的突變,模糊了或掩蓋了圖像的細(xì)節(jié),但是很多臨床診斷至關(guān)重要的是醫(yī)學(xué)超聲圖像的細(xì)節(jié)信息。因而,斑點(diǎn)是醫(yī)學(xué)超聲B模式圖像低對比度的主要原因之一,它可以被看作是一個噪聲源,應(yīng)當(dāng)抑制。在臨床醫(yī)學(xué)診斷中超聲成像技術(shù)應(yīng)用很廣泛,但是因?yàn)槭芟到y(tǒng)成像機(jī)制的影響,超聲成像技術(shù)形成的圖像比較容易形成斑點(diǎn)噪聲,這將導(dǎo)致后期圖像分析工作的要求難以滿足。為了提高圖像對比度,醫(yī)學(xué)超聲圖像斑點(diǎn)去噪技術(shù)已經(jīng)得到發(fā)展,可以保留圖像的邊緣,抑制斑點(diǎn)噪聲,使得臨床醫(yī)生能準(zhǔn)確地識別和分析病變區(qū)域。因此,醫(yī)學(xué)超聲圖像去噪技術(shù)研究對臨床診斷具有重要的現(xiàn)實(shí)意義。本文首先簡單介紹了超聲成像原理、超聲B模式成像、超聲斑點(diǎn)噪聲模型以及去斑性能評價標(biāo)準(zhǔn)等,然后分析了幾種經(jīng)典的超聲斑點(diǎn)抑制算法,如斑點(diǎn)抑制各項(xiàng)異性擴(kuò)散方法(SRAD)、細(xì)節(jié)保留各項(xiàng)異性擴(kuò)散方法(DPAD)、雙邊濾波(BF)和P-M模型。針對醫(yī)學(xué)超聲圖像中降低圖像質(zhì)量及導(dǎo)致診斷困難的斑點(diǎn)噪聲的顆粒模型特征,本文提出了基于分?jǐn)?shù)階的醫(yī)學(xué)超聲圖像降噪方法,為了保留更多的紋理信息,基于具有k(阻止擴(kuò)散的梯度閾值)和v(分?jǐn)?shù)階階數(shù))平衡關(guān)系的分?jǐn)?shù)階偏微分方程的圖像去噪模型被構(gòu)建,它有效結(jié)合了分?jǐn)?shù)微積分理論和偏微分方程方法,并且通過分?jǐn)?shù)階掩模算子實(shí)現(xiàn)了它的數(shù)值計(jì)算方法。與其他三種傳統(tǒng)的超聲去噪方法(P-M模型、SRAD和DPAD)相比,本文提出的基于分?jǐn)?shù)階的各向異性擴(kuò)散算法(FAD),在去除斑點(diǎn)噪聲的同時保留組織結(jié)構(gòu)方面更有優(yōu)勢。在產(chǎn)生相同實(shí)驗(yàn)結(jié)果的條件下,本文提出的算法比雙邊濾波(BF)運(yùn)行速度更快。醫(yī)學(xué)超聲體模圖像和人體成像實(shí)驗(yàn)表明,基于分?jǐn)?shù)階的各向異性擴(kuò)散方法可以提高組織的信噪比和超聲B模式圖像的質(zhì)量。
[Abstract]:Medical ultrasound imaging has become one of the most important diagnostic tools because of its advantages of low cost, high efficiency, real-time, convenient and safe. However, speckle noise superimposed by granular structures is widely found in medical ultrasound B-mode images. The noise appears as a mutation of pixel gray value, which obscures or conceals the details of the image. But many clinical diagnoses are critical to the details of medical ultrasound images. Therefore, speckle is one of the main reasons for the low contrast of B-mode medical ultrasound images. It can be regarded as a noise source and should be suppressed. Ultrasonic imaging technology is widely used in clinical medical diagnosis, but because of the influence of system imaging mechanism, the image formed by ultrasonic imaging technology is easy to form speckle noise, which will lead to the later stage of image analysis difficult to meet the requirements. In order to improve image contrast, medical ultrasound image speckle denoising technology has been developed, which can preserve the edge of the image, suppress speckle noise, and enable clinicians to accurately identify and analyze the lesion area. Therefore, the study of medical ultrasound image denoising technology has important practical significance for clinical diagnosis. In this paper, the principle of ultrasonic imaging, ultrasonic B-mode imaging, ultrasonic speckle noise model and evaluation criteria of speckle removal are briefly introduced, and then several classical algorithms for ultrasonic speckle suppression are analyzed. For example, speckle suppression of heterosexual diffusion methods (SRADX), detail retention of various heterosexual diffusion methods (DPADX), bilateral filtering (BF) and P-M model. In order to preserve more texture information, a fractional-order image de-noising method is proposed to reduce the image quality and the speckle noise in medical ultrasound images. The image denoising model of fractional partial differential equation with k (gradient threshold to prevent diffusion) and v (fractional order) equilibrium is constructed, which effectively combines fractional calculus theory with partial differential equation method. The numerical calculation method is realized by fractional mask operator. Compared with the other three traditional ultrasonic denoising methods, SRAD and DPAD, the fractional order anisotropic diffusion algorithm proposed in this paper has more advantages in removing speckle noise while preserving the structure of the tissue. Under the same experimental results, the proposed algorithm is faster than the two-sided filter. Medical ultrasound phantom images and human body imaging experiments show that fractional order anisotropic diffusion method can improve the signal-to-noise ratio of tissues and the quality of B-mode ultrasound images.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R310;TP391.41

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