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Basic study of computer diagnosis of high precision chest x-ray images Using digital radiography

数字放射线摄影高精度胸部X线图像计算机诊断的基础研究

基本信息

批准号：
62460125
负责人：
TORIWAKI Jun-ichiro
金额：
$ 4.29万
依托单位：
Nagoya University
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1987
资助国家：
日本
起止时间：
1987 至 1988
项目状态：
已结题

项目摘要

(1) Our first aim in this project is to improve the performance of AISCR-V3(Automated Interpretation System of Chest Radiograms - Version 3) which we developed, so that it may have enough ability to treat high quality images taken by recent digital radiography (DR). We extended the picture size the system can process from 300 x 300 pixels to 600 x 600 pixels. We developed a new procedure to recognize vessel shadows using a position variant contast filter, and improved the ability to detect abnormal shfdows in the lung.(2) Concerning computer diagnosis of pneumoconiosis. we newly developed a procedure to recognize small rounded opacities in the lung and measure the density of those opacities, by employing a difference type filtering followed by a patten classification algorithm. By combining the set of the same type of filters with different mask sizes we derived a procedure to execute both the density classification and the size classification of pneumoconiosis in a unified way. We applied the procedure to the ILO international standard film set with the promising result. Furthermore we tried the recognition of rounded opacities from x-ray CT images of pneumoconiosis and showed its feasibility.(3) Two kinds of binary operations two pictures were applied computer diagnosis of chest x-ray images. One is detection of lung cancer from energy subtraction DR images. This revealed characteristics of energy subtraction images and the feasibility of computer interpretation of such images. The other is automated detection and measurement of the amount of changes among picture, sequences taken at different times from the same patient. We developed a procedure consisting of registration by the affine transformation and change detection by the local cross correlation. and applied it to the lung cancer diagnosis.

(1)我们在这个项目中的第一个目标是提高我们开发的AISCR-V3（胸片自动判读系统-版本3）的性能，以便它有足够的能力处理最近的数字X射线摄影（DR）拍摄的高质量图像。我们将系统可以处理的图片大小从300 x 300像素扩展到600 x 600像素。我们开发了一种新的程序来识别血管阴影，使用位置可变的对比度滤波器，并提高了检测肺中异常shffallen的能力。(2)关于尘肺病的计算机诊断。我们新开发了一种过程，通过采用差分类型滤波，然后采用模式分类算法，来识别肺中的小圆形阴影，并测量这些阴影的密度。通过将具有不同掩模尺寸的相同类型的滤波器的集合相结合，我们导出了以统一的方式执行尘肺的密度分类和尺寸分类的过程。将该方法应用于国际劳工组织（ILO）国际标准胶片集，取得了良好的效果.并对尘肺X线CT图像中圆形阴影的识别进行了尝试，证明了该方法的可行性。(3)采用两种二值化运算两张图片对胸部X线图像进行计算机诊断。一种是从能量减影DR图像检测肺癌。这揭示了能量减影图像的特征和计算机解释这种图像的可行性。另一种是自动检测和测量同一患者在不同时间拍摄的图像序列之间的变化量。我们开发了一个程序，包括注册的仿射变换和变化检测的局部互相关。并将其应用于肺癌的诊断。