计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
20期
171-175,210
,共6页
肿块分割%图像预处理%梯度%自适应区域生长
腫塊分割%圖像預處理%梯度%自適應區域生長
종괴분할%도상예처리%제도%자괄응구역생장
mass segmentation%image preprocessing%gradient%adaptive region growing
乳腺X图像中肿块特征的复杂多变，给肿块的分割带来了很大困难，区域生长为肿块分割提供了一种比较可靠的方法。传统的区域生长由于生长次数和准则比较单一，就会出现较多的过生长和欠生长，从而影响其分割精度和可靠性，针对这一问题，提出了一种利用自适应区域生长对乳腺肿块进行分割的方法。对肿块感兴趣区域进行背景去除和领域抑制得到预处理后的图像，利用预处理后图像各像素个数确定区域生长的种子点，再利用肿块图像的梯度分布及变化趋势确定自适应区域生长是否过边缘，从而确定最佳生长准则。实验结果表明，相对于三层地形分割算法及模型分割算法，自适应区域生长算法分割得更准确、可靠。
乳腺X圖像中腫塊特徵的複雜多變，給腫塊的分割帶來瞭很大睏難，區域生長為腫塊分割提供瞭一種比較可靠的方法。傳統的區域生長由于生長次數和準則比較單一，就會齣現較多的過生長和欠生長，從而影響其分割精度和可靠性，針對這一問題，提齣瞭一種利用自適應區域生長對乳腺腫塊進行分割的方法。對腫塊感興趣區域進行揹景去除和領域抑製得到預處理後的圖像，利用預處理後圖像各像素箇數確定區域生長的種子點，再利用腫塊圖像的梯度分佈及變化趨勢確定自適應區域生長是否過邊緣，從而確定最佳生長準則。實驗結果錶明，相對于三層地形分割算法及模型分割算法，自適應區域生長算法分割得更準確、可靠。
유선X도상중종괴특정적복잡다변，급종괴적분할대래료흔대곤난，구역생장위종괴분할제공료일충비교가고적방법。전통적구역생장유우생장차수화준칙비교단일，취회출현교다적과생장화흠생장，종이영향기분할정도화가고성，침대저일문제，제출료일충이용자괄응구역생장대유선종괴진행분할적방법。대종괴감흥취구역진행배경거제화영역억제득도예처리후적도상，이용예처리후도상각상소개수학정구역생장적충자점，재이용종괴도상적제도분포급변화추세학정자괄응구역생장시부과변연，종이학정최가생장준칙。실험결과표명，상대우삼층지형분할산법급모형분할산법，자괄응구역생장산법분할득경준학、가고。
Since there are a lot of complex and changing characteristics of mass in mammography with great difficulty in mass segmentation, region growing becomes a reliable method to accomplish it. An adaptive region growing method for mass segmentation is presented so as to improve its precision and reliability and reduce the over-growing and lack-growing when dealing with different images in one principle. Background removing and region suppression are used to preprocess the Region Of Interest(ROI)of mass, and then it uses the number of image pixels to determine the seed point for region growing, and determines whether the adaptive region growing is out of edge through the gradient distribution and tends of mass ROI in order to obtain the best growth criteria. The experimental results show that the adaptive region growing algo-rithm for segmentation compared to the three-terrain segmentation algorithm and model segmentation algorithm is more accurate and reliable.
