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数字X线摄影中的图像特征分析与计算机辅助诊断:胸部图像中气胸的自动检测

Image feature analysis and computer-aided diagnosis in digital radiography: automated detection of pneumothorax in chest images.

作者信息

Sanada S, Doi K, MacMahon H

机构信息

Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, University of Chicago, Illinois 60637.

出版信息

Med Phys. 1992 Sep-Oct;19(5):1153-60. doi: 10.1118/1.596790.

Abstract

In order to aid radiologists in the diagnosis of pneumothorax from chest radiographs, an automated method for detection of subtle pneumothorax is being developed. The computerized method is based on the detection of a fine curved-line pattern, which is a unique feature of radiographic findings of pneumothorax. Initially, regions of interest (ROIs) are determined in each upper lung area, where subtle pneumothoraces commonly appear. The pneumothorax pattern is enhanced by the selection of edge gradients within a limited range of orientations. Rib edges included in this edge-enhanced image are removed, based on the locations of posterior ribs that are determined separately. A subtle curved line due to pneumothorax is then detected by means of the Hough transform. The detected pneumothorax pattern is marked on the chest image displayed on a CRT monitor. With the present computer method applied to 50 chest images (28 normals and 22 abnormals with pneumothorax), we were able to detect 77% of pneumothoraces, with 0.44 false-positives per image.

摘要

为了帮助放射科医生从胸部X光片中诊断气胸,正在开发一种自动检测细微气胸的方法。该计算机化方法基于对一种精细曲线模式的检测,这是气胸影像学表现的一个独特特征。最初,在每个上肺区域确定感兴趣区域(ROI),细微气胸通常出现在这些区域。通过在有限的方向范围内选择边缘梯度来增强气胸模式。根据单独确定的后肋位置,去除该边缘增强图像中包含的肋骨边缘。然后通过霍夫变换检测由气胸引起的细微曲线。检测到的气胸模式会标记在阴极射线管(CRT)显示器上显示的胸部图像上。将目前的计算机方法应用于50张胸部图像(28张正常图像和22张气胸异常图像)时,我们能够检测出77%的气胸,每张图像有0.44个假阳性。

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