Computer-aided diagnosis system for lung tumors

Hideo Suzuki; Noriko Inaoka; Hirotsugu Takabatake; Masaki Mori; Hiroshi Natori

doi:10.1117/12.237912

16 April 1996 Computer-aided diagnosis system for lung tumors

Hideo Suzuki, Noriko Inaoka, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori

Proceedings Volume 2710, Medical Imaging 1996: Image Processing; (1996) https://doi.org/10.1117/12.237912
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

This paper describes a computerized system of tumor detection for lung cancer diagnosis. Through the ten years study, we developed some key algorithms for computer-aided diagnosis. The most important algorithm is a filter to detect suspicious shadows of tumor on a plain chest x-ray image. The filter is named directional contrast filter for nodule (DCF-N). The DCF-N is highly sensitive to ambiguous shadows such as malignant tumors. And we developed a rule- based system to eliminate false-positive shadows. In our study, the system was effective to eliminate shadows of blood vessels and ribs which were primary groups of false-positives. Our current research is focusing on the development of the automatic tumor detection system for lung cancer examination by using CT images. In this paper, we discuss whether the system for plain chest x-ray images can apply to spiral CT images within a malignant tumor, which are reconstructed at 2 mm or 5 mm slice thickness. About a trial case, although the DCF-N can detect the malignant tumor, some false-positives are also detected. As to the analysis of the shadows, which are detected by the DCF-N, the major false-positives are blood vessels shadows. Therefore, the rule to eliminate blood vessels shadows in the rule-base for plain x- ray images is also effective for the CT images.

Citation Download Citation

Hideo Suzuki, Noriko Inaoka, Hirotsugu Takabatake, Masaki Mori, and Hiroshi Natori "Computer-aided diagnosis system for lung tumors", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.237912

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