An image analyzing system for interstitial lung abnormalities in chest radiography. Detection and classification by Laplacian-Gaussian filtering and linear opacity judgment.
OBJECTIVE
The effectiveness of a computerized analysis system to detect and characterize interstitial lung abnormalities seen on chest radiographs was evaluated. This method included a process of four-directional Laplacian-Gaussian filtering and a process of linear opacity judgement. For quantitative analysis of interstitial opacities, the radiographic index, which is the percentage of opacity areas in a region of interest, was obtained and evaluated in the images. These opacities represented interstitial lung abnormalities.


METHODS
Two regions of interest were selected in each right lung of 50 patients with normal lung parenchyma and 50 patients with diffuse interstitial lung abnormalities, confirmed with high-resolution computed tomography. These regions of interest were processed by our computerized analysis system.


RESULTS
Abnormal lungs were well differentiated from normal lungs by the radiographic indices obtained from the images filtered by four-directional Laplacian-Gaussian filters and from those processed by linear opacity judgement. However, honeycomb lesions and other interstitial abnormalities (interstitial changes other than honeycombing) were differentiated from each other only by the radiographic indices obtained from the image processed by linear opacity judgment (P < .05).


CONCLUSIONS
These results indicate that this system is useful for the detection and characterization of interstitial lung abnormalities.
Kido
S
S
Department of Radiology, Osaka University Medical School, Japan.
Ikezoe
J
J
Naito
H
H
Masuike
M
M
Tamura
S
S
Kozuka
T
T
D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging*; D017563:Lung Diseases, Interstitial / Q000145:classification / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D014057:Tomography, X-Ray Computed