發(fā)布時間：2018-06-18 16:23

  本文選題：細胞篩選平臺 + 細胞圖像處理��； 參考：《河南科技大學》2017年碩士論文

【摘要】：國內(nèi)對細胞篩選平臺的研究較少,在生物細胞培養(yǎng)領域中一般采用96孔板作為培養(yǎng)基來培養(yǎng)細胞,由于96孔板內(nèi)的細胞群落較小,肉眼難以分別,細胞篩選工作需要在顯微鏡下觀測,面臨著篩選檢出率低、人工篩選易疲勞,手動對焦耗時耗力等問題。針對此問題,設計細胞篩選平臺,研究細胞篩選平臺顯微自動對焦系統(tǒng),包括細胞篩選平臺的建立,運動控制系統(tǒng)的設計,顯微自動對焦系統(tǒng)圖像預處理以及自動對焦相關算法的優(yōu)化。首先,在機構滿足的前提下,細胞篩選平臺通過控制單元的驅(qū)動,實現(xiàn)倒置生物顯微鏡載物臺的自動進給和步進功能,其次,根據(jù)CCD所拍攝圖像的清晰程度反饋至自動對焦處理單元,實現(xiàn)物鏡的垂直進給,從而實現(xiàn)顯微自動對焦系統(tǒng)的運行。論文分析細胞篩選平臺顯微自動對焦的工作原理和設計方法;研究顯微自動對焦系統(tǒng)中對焦窗口的選取方法;傳統(tǒng)的自動對焦區(qū)域選取方法對細胞顯微圖像進行對焦時,由于對焦區(qū)域的位置和大小固定,且細胞屬于隨機分布,并不總是處于圖像的中心區(qū)域,導致對焦不準,忽略主體細胞群落,針對此問題,采用改進的魚群算法,增加繁殖、淘汰行為,避免出現(xiàn)局部最優(yōu)解的情況,提出一種基于魚群算法的自動對焦窗口選取方法;通過對傳統(tǒng)的對焦窗口選取方法和魚群算法所獲得的對焦窗口內(nèi)圖像,分別與改進后的魚群取窗法進行對比分析,結果表明:改進后的魚群取窗法所獲得的圖像包含更多的細節(jié),且能自適應地尋找目標主體,并生成對焦區(qū)域;對焦區(qū)域內(nèi)包含的圖像經(jīng)傅里葉變換函數(shù)處理后,其高頻數(shù)量更多,得到了具有更高清晰度的圖像。采用傳統(tǒng)的自動對焦梯度函數(shù)評價算法在對顯微圖像進行自動對焦時,細胞顯微圖像中的細胞邊緣灰度值梯度變化較小,對焦時易受到噪聲影響。將Sobel梯度函數(shù)增加至4個方向算子模板;根據(jù)信號疊加原理,將符合Gaussian分布的Sobel4direction梯度函數(shù)在Brenner梯度函數(shù)上加權疊加,改變數(shù)據(jù)分布的離散程度,提出一種改進的Sobel梯度函數(shù)自動對焦評價算法,提高對焦精度;通過對傳統(tǒng)自動對焦梯度函數(shù)和改進后梯度函數(shù)進行對比實驗后,結果表明:改進后的自動對焦評價算法較傳統(tǒng)的能更好的抑制噪聲,電機在爬山算法的搜索對焦中具有更小的對焦搜索區(qū)間范圍,獲得的圖像清晰度也更高。論文的研究結果對闡明細胞篩選平臺的機理,揭示顯微自動對焦系統(tǒng)中對焦精度的提高和對焦窗口的選取規(guī)律具有重要意義,可以為細胞篩選識別與分類奠定基礎,在生物細胞工程方面具有重要的應用前景。
[Abstract]:In the field of biological cell culture, 96-well plate is generally used as the culture medium for cell culture. Because the cell community in the 96-well plate is small, it is difficult for naked eye to separate, because of the small cell community in the 96-well plate. The work of cell screening needs to be observed under microscope. It is faced with the problems of low detection rate, easy fatigue of manual screening, time and energy consumption of manual focusing, and so on. In order to solve this problem, the cell screening platform is designed, and the microscopic autofocus system of cell screening platform is studied, including the establishment of cell screening platform, the design of motion control system, Image preprocessing and optimization of autofocus correlation algorithm for micro-automatic focusing system. First of all, under the premise that the mechanism is satisfied, the cell screening platform realizes the automatic feed and step function of the inverted biological microscope platform through the drive of the control unit. Secondly, According to the clarity of the image taken by CCD, the automatic focus processing unit is fed back to realize the vertical feed of the objective lens, thus realizing the operation of the micro-automatic focusing system. This paper analyzes the working principle and design method of microscopical auto-focusing on cell screening platform, studies the selection method of focusing window in micro-automatic focusing system, and focuses on the cell microscopic image by traditional auto-focusing region selection method. Because of the fixed position and size of the focus region and the random distribution of the cells, they are not always in the center of the image, which leads to inaccurate focus and neglects the main cell community. In order to solve this problem, the improved fish swarm algorithm is adopted to increase the propagation. In order to avoid the occurrence of local optimal solution, an automatic focusing window selection method based on fish swarm algorithm is proposed, and the image in the focus window is obtained by traditional focusing window selection method and fish swarm algorithm. Compared with the improved fish group window extraction method, the results show that the image obtained by the improved fish group window extraction method contains more details, and it can find the target subject adaptively and generate the focus region. After the image contained in the focus region is processed by Fourier transform function, the high frequency quantity of the image is more, and the image with higher definition is obtained. Using the traditional automatic focusing gradient function evaluation algorithm, the grayscale gradient of the cell edge in the microscopic image changes little, and is easily affected by noise when focusing on the microscopic image. The Sobel gradient function is increased to four directional operator templates, and the Sobel4direction gradient function, which conforms to Gaussian distribution, is weighted on the Brenner gradient function according to the signal superposition principle, which changes the dispersion of the data distribution. An improved automatic focusing evaluation algorithm of Sobel gradient function is proposed to improve the focusing accuracy. The results show that the improved auto-focus evaluation algorithm can suppress noise better than the traditional one, and the motor has a smaller focus range and higher image clarity in the search focus of the mountain climbing algorithm. The results of this paper are of great significance to clarify the mechanism of cell screening platform, to reveal the improvement of focusing accuracy and the selection rule of focusing window in micro-automatic focusing system, and to lay a foundation for cell screening recognition and classification. It has important application prospect in biological cell engineering.
【學位授予單位】：河南科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：Q813;TP391.41

【參考文獻】

相關期刊論文 前10條

1 商艷芝;江e，

本文編號：2036098