Development of Computer-Aided Diagnosis System in Screening Digital Chest Radiographs

数字化胸片筛查计算机辅助诊断系统的开发

• 批准号: 08671046
• 负责人: KATSURAGAWA Shigehiko
• 金额: $ 1.09万
• 依托单位: Iwate Medical University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1996
• 资助国家: 日本
• 起止时间: 1996 至 1997
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08671046/
• 关键词: screening chest radiography; computer-aided-diagnosis; digital radiography; Lung nodule; digital image processing; ディジタルラジオグラフィー

I have developed a system of computer-aided diagnosis (CAD) in screening digital chest radiography for improvement of detection accuracy of lung nodules. CAD refers to a diagnosis by a radiologist taking into consideration the results of an automated computer analysis of radiographic images as a "second opinion." In this project, I improved a computerized detection method of lung nodules, which was developed previously.In addition, I performed a preliminary research of temporal subtraction technique which can enhance the interval changes by subtracting a previous image from a current one.1.I derived a new detection algorithm which increases the contrast of lung nodules with various sizes by using matched filters. I applied this method for 200 chest radiographs with lung nodules in order to investigate the detection accuracy. The detection performance was 79% of true positive at 1.7 false positives/image.2.I derived a temporal subtraction technique with traslation, rotation and warping for matching previous and current images. I applied this technique for 876 pairs of previous and current images obtained by a mobile computed radiography (CR) system. 76.7% of subtraction images without misregistration artifacts were successfully provided.3.I provided an image database including approximately 10,000 pairs of previous and current images during the term of this project.4.My results indicates that this CAD system has a potential usefulness for radiologists to detect lung nodules in the screening chest radiography.

为了提高肺部结节的检测准确率，我开发了一套计算机辅助诊断(CAD)系统，用于筛选数字胸片。CAD指的是放射科医生在考虑到计算机自动分析放射图像的结果后做出的诊断，并将其作为“第二意见”。在本项目中，我改进了先前开发的一种肺结节的计算机化检测方法，并对时间相减技术进行了初步研究，该技术可以通过从当前图像中减去先前的图像来增强间隔变化。1.我推导了一种新的检测算法，该算法利用匹配滤波器来增强不同大小的肺结节的对比度。我将这种方法应用于200例肺部结节的胸部X线片，以考察其检测的准确性。在每幅图像1.7个假阳性的情况下，检测性能为真阳性的79%。2.我提出了一种结合平移、旋转和翘曲的时间减法技术，用于匹配以前和当前图像。我将这项技术应用于通过移动计算机放射成像(CR)系统获得的876对以前和现在的图像。76.7%的减影图像没有配准错误伪影。3.我在本项目期间提供了一个包含约10,000对以前和当前图像的图像数据库。4.我的结果表明，该计算机辅助设计系统对放射科医生在筛查胸部摄影中发现肺结节具有潜在的实用价值。

项目成果

T.Okabe: Radiological Science : 14 Medical Imaging. Ishiyaku Publishers Inc., Tokyo, 300 (1997)

T.Okabe：放射科学：14 医学成像。

T.Ishida: "Computerized analysis of interstitial disease in chest radiographs: Improvement of geometric-pattern feature analysis" Medical Physics. 24・6. 915-924 (1997)

T. Ishida：“胸部X光片中间质疾病的计算机化分析：几何图案特征分析的改进”医学物理学24・6（1997）。

Shigehiko Katsuragawa: "Computer-aided diagnosis of interstitial disease in digital chest radiographs : Classification of normal and abnormal lungs by rule-based method and artificial neural networks" Journal of Digital Imaging. 10・3. 108-114 (1997)

Shigehiko Katsurakawa：“数字胸部X光片中间质性疾病的计算机辅助诊断：通过基于规则的方法和人工神经网络对正常和异常肺部进行分类”《数字成像杂志》10・3（1997）。

Shigehiko Katsuragawa: "Computer-aided diagnosis of interstitial disease in digital chest radiographs : Classification of normal and abnormal lungs by rule-based method and artificial neural networks" Journal of Digital Imaging. 9・3. 137-144 (1996)

Shigehiko Katsurakawa：“数字胸部X光片中间质性疾病的计算机辅助诊断：通过基于规则的方法和人工神经网络对正常和异常肺部进行分类”《数字成像杂志》9・3（1996）。

Takayuki Ishida: "Computerized analysis of interstitial disease in chest radiographs : Improvement of geometric-pattern feature analysis" Medical Physics. 24・6. 915-924 (1997)

Takayuki Ishida：“胸部X光片中间质疾病的计算机化分析：几何图案特征分析的改进”医学物理学24・6（1997）。