Classification of lung tumors on chest radiographs by fractal texture analysis.
OBJECTIVE
The authors determine the usefulness of fractal texture analysis in classification of lung tumors on chest radiographs.


METHODS
A method of fractal texture analysis was applied for classification of lung tumors on digitized chest radiographs. It was performed in 15 cases of benign lesions and in 26 cases of malignant tumors. All lesions were proved by histology. For classification, the fractal distances of the tumors were calculated and an energy measure related to the variances as a second characteristic was applied. The results were compared with those of a conventional classification method based on the co-occurrence matrix.


RESULTS
Although the conventional method failed in classification of lung tumors, a clear separation between benign and malignant lesions was attained by fractal analysis. A differentiation between primary lung cancer and metastases was not possible.


CONCLUSIONS
The results of our study demonstrate the usefulness of fractal texture analysis for classification of lung tumors on chest radiographs.
Department of Diagnostic Radiology, University of Technology, Aachen, Germany.
J
J
Peiss
M
M
Verlande
W
W
Ameling
R W
RW
Günther
D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008171:Lung Diseases / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000556:secondary; D011856:Radiographic Image Enhancement