北京生物醫(yī)學(xué)工程

基于數(shù)學(xué)形態(tài)學(xué)的CT圖像肝臟腫瘤提取研究

Segmentation of liver tumors for CT images based on mathematical morphology

作者：劉耀輝黃展鵬鮑蘇蘇

單位：湘南學(xué)院教務(wù)處(湖南郴州 423000)

關(guān)鍵詞：數(shù)學(xué)形態(tài)學(xué)； CT圖像；分水嶺算法；肝臟腫瘤；控制標(biāo)記符

分類號：

出版年·卷·期（頁碼）：2012·31·3（237-240）

摘要：

目的肝臟腫瘤的提取是肝臟三維可視化、手術(shù)規(guī)劃和模擬的基礎(chǔ)，而當(dāng)前腫瘤分割存在干預(yù)過多和分割效果不佳的問題。方法本文通過對腹部CT圖像進(jìn)行高斯平滑以去除圖像噪聲和細(xì)密紋理，計算出圖像的形態(tài)學(xué)梯度并用高、低帽變換進(jìn)行增強(qiáng)，再根據(jù)用戶選擇點(diǎn)計算內(nèi)部和外部標(biāo)記符，然后基于控制標(biāo)記符的分水嶺算法分割圖像，提取出腹部CT圖像中的病變組織。結(jié)果實驗結(jié)果表明，該算法能夠在較少的人工干預(yù)下快速分割出肝臟病變組織。結(jié)論該算法實現(xiàn)了腹部CT圖像中肝臟病變組織的提取。

Objective Segmentation of the liver tumor regions based on abdominal CT scan images is a crucial step in 3D visualization，surgical planning and simulation. In order to solve the disadvantage of CT image segmentation and reduce the manual interaction of the liver tumor segmentation, a novel segmentation algorithm for liver tumors is proposed. Methods Firstly, the CT images are smoothed by Gaussian smoothing filter for removing noises and textures. Secondly, the gradients of the images are measured by mathematical morphology and enhanced by Top-hat transform and Bot-hat transform. Thirdly, internal marker-controlled and external marker-controlled are calculated by the points chosen by the users. Finally, the regions of liver tumors from CT scan images are extracted by the watershed algorithm based on the marker-controlled. Results Experimental results show that this method can effectively and quickly segment the liver tumors with less user interaction than other algorithms. Conclusions This method realizes the segmentation of liver tumors for abdominal CT scan images.

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