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畢業(yè)設(shè)計(jì)-基于x射線圖像的乳房腫塊計(jì)算機(jī)輔助檢測(cè)方法研究(已修改)

2024-12-19 19:10 本頁(yè)面
 

【正文】 哈爾濱工程大學(xué)本科生畢業(yè)論文 摘 要 乳腺癌是中老年婦女中發(fā)病率和死亡率最高的惡性腫瘤之一,其早發(fā)現(xiàn)及早治 療是提高治愈率和降低死亡率的關(guān)鍵。乳腺鉬 靶攝影是普查和診斷乳腺癌的最有效方法。但純?nèi)斯ら喿x 鉬靶 片存在易疲勞、耗時(shí)多、誤診和漏診率較大等問(wèn)題。利用計(jì)算機(jī)圖像處理技術(shù) 輔助檢測(cè) ,可以提高乳腺癌早期發(fā)現(xiàn)率和診斷準(zhǔn)確率,使得診斷結(jié)果更具有客觀性及精確性。 本文以乳房腫塊檢測(cè)展開(kāi),依照乳腺鉬靶 X 射線圖像 去噪、 乳腺鉬靶 X射線圖像去噪 增強(qiáng)、 可疑腫塊的分割 的次序,進(jìn)行了乳腺 鉬靶 X 線圖像乳房腫塊的輔助檢測(cè)研究。 在乳腺鉬靶 X 射線圖像去噪方面 , 針對(duì)乳腺 鉬靶 X 射線圖像的腫塊區(qū)域和背景區(qū)域都有較大噪聲 , 影響閱片 的問(wèn)題 ,本 文提出 了基于小波變換的 軟閾值化去噪方法,在保持診斷影像特征特別是給定輪廓線內(nèi)的毛刺和小葉征象的前提下,消除了噪聲和 偽影 帶來(lái)的影響 。 在乳腺鉬靶 X 射線 圖像增強(qiáng)方面 , 本文 采取了 簡(jiǎn)單實(shí)用的直方圖均衡化 方法使乳腺鉬靶 X 射線圖像對(duì)比度低的問(wèn)題得到了很好的解決 。 對(duì)于 可疑腫塊 的 分割, 本文采取了基于水平集理論的窄帶算法,實(shí)現(xiàn)了全自動(dòng)和半自動(dòng)的分割處理, 通過(guò)幾十組良性和惡性腫瘤圖像數(shù)據(jù)的測(cè)試,程序 可以 使 腫塊區(qū)域 準(zhǔn)確 地 從乳腺區(qū)域分割 出來(lái)。 關(guān)鍵詞: 乳房腫塊;鉬靶 X 射線;小波變換;直方圖均衡化;水平集分割 哈爾濱工程大學(xué)本科生畢業(yè)論文 ABSTRACT Breast cancer is one of the most mon malignancies with high incidence and mortality rates among older women. To increase the cure rate and reduce the mortality from this disease, early detection and treatment of breast cancer is the important premise. Mammography is considered as the most reliable and costeffective method for early screening and diagnosis of breast cancer. But the problems, such as fatigue, timeconsuming, higher rates of misdiagnosis and missed diagnosis, will occur if the detection of breast cancer is solely performed by a single radiologist. Computeraided detection, which is based on puter image processing techniques, has the potential to improve the rate of early detection and make diagnosis results more objective and accurate. This dissertation, rooting from the detection of breast lumps, with the sequence of breast Xray images denoising, Xray images enhancement, segmentation of suspicious mass, make a series study about aided detection of breast lumps. For mammography Xray image denoising, to reduce the noise in the mammography of breast mass regions and background regions, this dissertation presents a waveletbased softthresholding denoising method, while maintaining diagnostic imaging features, especially within a given contour and the burr under the premise of lobular signs, eliminating the noise and the impact of artifacts. For mammography Xray in image enhancement, this paper adopted a simple and practical method of histogram equalization and found a good solution to the problem of mammography Xray image of low contrast. For the segmentation of suspicious mass, this theory has taken the narrowband level set based algorithm to achieve a fully automatic and semiautomatic segmentation, benign and malignant tumors through the dozens of groups of test image data, the program can make the tumor region from the breast region accurately split out. Key words: breast mass。 mammogram。 wavelet transform。 histogram 哈爾濱工程大學(xué)本科生畢業(yè)論文 equalization。 level set segmentation 哈爾濱工程大學(xué)本科生畢業(yè)論文 目 錄 第 1章 緒論 .......................................................................................1 研究的背景 、目的 及意義 .......................................................................... 1 國(guó)內(nèi)外研究現(xiàn)狀 .......................................................................................... 3 本文主要的研究工作 .................................................................................. 6 論文結(jié)構(gòu) ...................................................................................................... 6 第 2章 乳腺癌和鉬靶 X射線圖像 ...................................................8 乳腺癌的概述 .............................................................................................. 8 乳腺癌的診斷方法 ...................................................................................... 8 乳腺癌鉬靶 X 射線影像特點(diǎn)分析 ............................................................11 乳腺影像對(duì)應(yīng)病理特征分析 ..............................................................11 鉬靶 X 射線影像的診斷難點(diǎn) ............................................................ 14 本章小結(jié) .................................................................................................... 16 小波去噪 .................................................................................................... 17 小波去噪的優(yōu)勢(shì) ................................................................................. 17 基于小波變換的閾值化去噪算法 ..................................................... 20 實(shí)驗(yàn)結(jié)果 ............................................................................................. 23 直方圖均衡化 ............................................................................................ 24 直方圖均衡化原理概述和算法流程 ................................................. 24 實(shí)驗(yàn)結(jié)果 ............................................................................................. 25 本章小結(jié) .................................................................................................... 27 第 4章 乳腺可疑腫塊區(qū)域分割 ..................................................... 28 醫(yī)學(xué)圖像分割的概念、分類(lèi)和研究現(xiàn)狀 ................................................ 28 水平集方法理論基礎(chǔ) ................................................................................ 29 水平集窄帶算法流程 ................................................................................ 32 實(shí)驗(yàn)結(jié)果 .................................................................................................... 34 哈爾濱工程大學(xué)本科生畢業(yè)論文 本章小結(jié) .................................................................................................... 37 結(jié)論 .................................................................................................................. 38 參考文獻(xiàn) ........................................................................................................ 39 致謝 .................................................................................................................. 43 哈爾濱工程大學(xué)本科生畢業(yè)論文 1 第 1章 緒論 隨著經(jīng)濟(jì)的快速發(fā)展和國(guó)民生活水平的不斷提高,人們生活方式發(fā)生了巨大變化,我國(guó)己成為乳腺癌發(fā)
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