基于DICOM格式的肝臟腫瘤CT圖像分割
黃荔麗, 王博亮, 黃曉陽
（廈門大學(xué) 計算機科學(xué)系，福建 廈門 361005）
摘 要:為減少數(shù)據(jù)損失與處理時間，直接從DICOM格式的CT胸腹部圖像中分割出肝臟腫瘤。為有效地分割出腫瘤，先設(shè)置恰當(dāng)?shù)拇皩挻拔弧＠肐TK讀取圖像，用均值曲率流濾波法去除圖像上的噪聲。對目前幾種在圖像分割領(lǐng)域應(yīng)用較多的閾值分割及區(qū)域生長分割算法進(jìn)行了探討，結(jié)合獲得的活體CT圖像進(jìn)行實驗研究，得到較為滿意和有效的結(jié)果。實驗表明：肝臟腫瘤這一目標(biāo)區(qū)域的面積較小，區(qū)域生長分割算法中的“置信連接閾值法”能從胸腹腔CT圖像中很好地分割出肝臟腫瘤。
關(guān)鍵詞：CT圖像; 閾值分割; 區(qū)域生長
中圖分類號： 文獻(xiàn)標(biāo)識碼： 文章編號：1673-629X(2008)01-0048-04
Segmentation of Liver Tumor in CT Image Based on DICOM Format
HUANG Li-li, WANG Bo-liang, HUANG Xiao-yang
(Computer Science Department ,Xiamen University, Xiamen 361005,China)
Abstract: For reducing data loss and proceeding time, liver tumor is directly segmented from thorax an d abdominal part in CT image based on DICOM format. Proper window width and window center are set first for efficient segmentation. ITK software is used to read the image, and curvature flow smoothing filter is used to denoise the image. Several histogram and region growing segmentation algorithms requently applied in image segmentation field are discussed, and also experimented combined with vivo CT image. Finally satisfied and effective result is obtained, which shows that the area of liver tumor in the image is small, so the target can be availably segmented by “confidence connected threshold method” in region growing
Key words: CT image; histogram segmentation; region growing |
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