【正文】 都會感到恐懼，癌癥是當(dāng)今世界上最常見的致命疾病之一，世界上每年都有很多人死于癌癥，并且發(fā)病率仍在逐年上升。癌癥的治療取決于對他早期的診斷，早期是治療癌癥的最佳時期。 因為癌細(xì)胞和非癌細(xì)胞對于病理專家在傳統(tǒng)的顯微鏡下觀察切片或涂片的方法下很難進行區(qū)分，借助現(xiàn)代計算機技術(shù)結(jié)合病理專家實踐經(jīng)驗，采用圖像處理技術(shù)對醫(yī)學(xué)圖像 進行處理，可以提高判斷的有效性和圖像信息的使用效率，從而對癌細(xì)胞進行更加準(zhǔn)確的識別。 數(shù)字圖像處理技術(shù)已被廣泛應(yīng)用到生物醫(yī)學(xué)領(lǐng)域，運用計算機對圖像進行處理和分析，并進一步完成癌細(xì)胞的檢測與識別，能有效的協(xié)助醫(yī)生對腫瘤癌癥做出診斷。近年來國內(nèi)外醫(yī)學(xué)圖像研究者對癌細(xì)胞的檢測識別提出了很多理論和方法，對癌細(xì)胞的診斷具有十分 重要的意義和實踐價值。經(jīng)典的邊緣檢測算子如 Sobel 算子， Laplacian 算子等利用圖像的每個像素鄰域內(nèi)灰度的變化來檢測邊緣。 關(guān)鍵詞 ：癌細(xì)胞，邊緣檢測，最佳閾值，輪廓提取 ， 數(shù)字圖像處理 河南科技大學(xué)本科畢業(yè)設(shè)計（論文） III CANCER CELL EDGE DETECTION (BASED ON ITERATIVE ALGORITHM AND CORROSION ALGORITHM, CONTOUR EXTRACTION) ABSTRACT Many people will me ntion cancer fear, cancer is one of the most mon fatal diseases in the world today the world every year many people die of cancer, and incidence rate is still increasing every year. The treatment of cancer depends on the diagnosis of his early, early is the best period of the treatment of cancer. The time of diagnosis of most cases of cancer are now belong to the late, lost the best time to cure, so the accurate early diagnosis and treatment has bee an urgent need to address the problem. Cancer cells and noncancer pathology experts in a traditional microscope to observe the biopsy or smear difficult to distinguish, with the help of modern puter technology, bined with practical experience of the pathologist, medical image processing using image processing technology, can improve to judge the effectiveness and efficiency in the use of the image information and thus more accurate identification of cancer cells. This has practical significance and broad prospects for medical research and teaching, and clinical diagnosis. Digital image processing technique has been widely applied to the biomedical field, the use of puter image processing and analysis, and plete detection and recognition of cancer cells can help doctors make a diagnosis of tumor cancers. Need to be made in the identification of cancer cells, the quantitative results, the human eye is difficult to accurately plete such work, and the use of puter image processing to plete the analysis and identification of the microscopic images have made great progress. In recent 河南科技大學(xué)本科畢業(yè)設(shè)計（論文） IV years, domestic and foreign medical images of cancer cells testing to identify the researchers put forward a lot of theory and method for the diagnosis of cancer cells has very important meaning and practical value. Cell edge detection is the cell area of the number of roundness and color, shape and chromaticity calculation and the basis of the analysis their test results directly affect the analysis and diagnosis of the disease. Classical edge detection operators such as Sobel operator, Laplacian operator, each pixel neighborhood of the image gray scale changes to detect the edge. Although these operators is simple, fast, but there are sensitive to noise, get isolated or in short sections of a continuous edge pixels, overlapping the adjacent cell edge defects, while the optimal threshold segmentation and contour extraction method of bining edge detection, obtained by the iterative algorithm for the optimal threshold for image segmentation, contour extraction algor ithm, digging inside the cell pixels, the last remaining part of the image is the edge of the cell, change the processing order of the traditional edge detection algorithm, by MATLAB programming, the experimental results that can effectively suppress the noise impact at the same time be able to objectively and correctly select the edge detection threshold, precision cell edge detection. KEY WORDS： The cancer cells, edge detection, and optimal threshold, contour extraction, digital image processing河南科技大學(xué)本科畢業(yè)設(shè)計（論文） V 畢業(yè)論文（設(shè)計）原創(chuàng)性聲明 本人所呈交的畢業(yè)論文（設(shè)計） 是我在導(dǎo)師的指導(dǎo)下進行的研究工作及取得的研究成果。對本論文（設(shè)計）的研究做出重要貢獻的個人和集體，均已在文中作了明確說明并表示謝意。有權(quán)將論文（設(shè)計）用于非贏利目的的少量復(fù)制并允許論文（設(shè)計）進入學(xué)校圖書館被查閱。保密的論文（設(shè)計）在解密后適用本規(guī)定。 ：任務(wù)書、開題報告、外文譯文、譯文原文（復(fù)印件）。圖表整潔，布局合理，文字注釋必河南科技大學(xué)本科畢業(yè)設(shè)計（論文） VII 須使用工程字書寫，不準(zhǔn)用徒手畫 3）畢業(yè)論文須用 A4 單面打印，論文 50 頁以上的雙面打印 4）圖表應(yīng)繪制于無格子的頁面上 5）軟件工程類課題應(yīng)有程序清單，并提供電子文檔 1）設(shè)計（論 文） 2）附件：按照任務(wù)書、開題報告、外文譯文、譯文原文（復(fù)印件）次序裝訂 3）其它 河南科技大學(xué)本科畢業(yè)設(shè)計（論文） VIII 目 錄 前 言 ................................................................................................... 1 第 1 章 圖像處理基礎(chǔ) ......................................................................... 3 167。 圖像灰度化 .............................................................................. 5 167。 鄰域平均濾波 ................................................................... 6 167。 邊緣檢測概述 .......................................................................... 9 167。 Robert 算子 ...................................................................... 10 167。 Krisch 算子 ...................................................................... 10 167。 Canny 算子 ..................................................................... 11 167。3 .1 迭代算法概述 ........................................................................ 13 應(yīng)用舉例 ........................................................................... 13 167。 腐蝕算法 ................................................................................ 15 集合論方法的理論基礎(chǔ) ................................................... 15 圖像的腐蝕 ....................................................................... 16 167。 邊緣檢測的 MATLAB 實現(xiàn) .................................................. 18 167。 實例結(jié)果 ................................................................................ 22 結(jié) 論 ................................................................................................. 25 參考文獻 ............................................................................................. 26 致 謝 ................................................................................................. 28 河南科技大學(xué)本科畢業(yè)設(shè)計（論文） 1 前 言 隨著計算機技術(shù)的不斷發(fā)展，對顯微鏡下細(xì)胞形態(tài)的自動圖