Computer-aided detection system of breast masses on ultrasound images
Computer-aided detection system of breast masses on ultrasound images
复制标题
超声图像乳腺肿块计算机辅助检测系统
DOI：
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Takako Morita
中科院分区：
文献类型：
--
作者：
Yuji Ikedo;D. Fukuoka;T. Hara;H. Fujita;E. Takada;T. Endo;Takako Morita
我们研究了计算机辅助检测（CAD）系统的乳腺肿块的筛选超声（US）图像。目前，国内外研究人员已经开发出了许多基于超声图像的计算机辅助检测和诊断系统。然而，一些方法在分析US图像时需要大量的计算时间，并且一些系统还需要放射科医师提前指示肿块。本文提出了一种利用边缘信息检测肿块的快速自动检测系统。我们的方法包括以下步骤：（1）噪声去除和图像归一化，（2）使用Canny边缘检测器检测到的垂直边缘来确定感兴趣区域（ROI），（3）使用分水岭算法分割ROI，以及（4）减少假阳性。本研究采用了11例全乳腺病例，共924张图像。所有病例在研究前均由放射科医生诊断。该数据库有11个恶性肿块。恶性肿块内部回声不均匀，回声低或等强，后方回声减弱或消失。使用所提出的方法，检测恶性肿块的灵敏度为90.9%（10/11），每幅图像的假阳性数为0.69（633/924）。它的结论是，我们的方法是有效的检测乳腺肿块的US图像。
We have investigated Computer-aided detection (CAD) system for breast masses on screening ultrasound (US) images. A lot of methods of Computer-aided detection and diagnosis system on US images have been developed by many researchers in the world. However, some methods require substantial computation time in analysing a US image, and some systems also need a radiologist to indicate the masses in advance. In this paper, we proposed fast automatic detection system which utilizes edge information in detecting masses. Our method consists of the following steps: (1) noise reduction and image normalization, (2) decision of the region of interest (ROI) using vertical edges detected by the canny edge detector, (3) segmentation of ROI using watershed algorithm, and (4) reduction of false positives. This study employs 11 whole breast cases with a total of 924 images. All the cases have been diagnosed by a radiologist prior to the study. This database have 11 malignant masses. These malignant masses have heterogeneous internal echo, a low or equal echo-level, and a deficient or disappearance posterior echo. Using the proposed method, the sensitivity in detecting malignant masses is 90.9% (10/11) and the number of false positives per image is 0.69 (633/924). It is concluded that our method is effective for detecting breast masses on US images.
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影响因子：
3.8
作者：
Horsch, K;Giger, ML;Vyborny, CJ
通讯作者：
Vyborny, CJ
影响因子：
3.8
作者：
Drukker, K;Giger, ML;Mendelson, EB
通讯作者：
Mendelson, EB
影响因子：
4.8
作者：
Drukker, K;Giger, ML;Mendelson, EB
通讯作者：
Mendelson, EB
影响因子：
3.8
作者：
Horsch, K;Giger, ML;Vyborny, CJ
通讯作者：
Vyborny, CJ