IMAGE FEATURE ANALYSIS AND COMPUTER-AIDED DIAGNOSIS IN DIGITAL RADIOGRAPHY .3. AUTOMATED DETECTION OF NODULES IN PERIPHERAL LUNG FIELDS
IMAGE FEATURE ANALYSIS AND COMPUTER-AIDED DIAGNOSIS IN DIGITAL RADIOGRAPHY .3. AUTOMATED DETECTION OF NODULES IN PERIPHERAL LUNG FIELDS
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DOI：
10.1118/1.596247
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发表时间：
1988-03-01
期刊：
影响因子：
3.8
通讯作者：
MACMAHON, H
中科院分区：
文献类型：
--
作者：
GIGER, ML;DOI, K;MACMAHON, H
我们正在研究肺结节的特征和周围正常的解剖背景，以便开发一种计算机视觉算法，用于在数字胸片上辅助检测结节。我们的技术包括尝试消除背景解剖结构在肺场通过差分图像的方法。然后，应用特征提取技术，如圆度、大小及其随阈值水平变化的测试，以便分离可疑结节。这种自动检测方案的初步结果在胸部周围肺区域产生高真阳性率和低假阳性率。这种检测方案可以帮助临床医生做出最终诊断，有可能提高肺癌的早期发现。
We are investigating the characteristic features of lung nodules and the surrounding normal anatomic background in order to develop an algorithm of computer vision for use as an aid in the detection of nodules in digital chest radiographs. Our technique involves an atempt to eliminate the background anatomic structures in the lung fields by means of a difference image approach. Then, feature-extraction techniques, such as tests for circularity, size, and their variation with threshold level, are applied so that suspected nodules can be isolated. Preliminary results of this automated detection scheme yield high true-positive rates and low false-positive rates in the peripheral lung regions of the chest. This detection scheme, which can assist a final diagnosis by the clinician, has the potential to improve the early detection of lung carcinomas.