Detection of Lung Nodule on Temporal Subtraction Images Based on Artificial Neural Network

Takumi Tokisa; Noriaki Miyake; Shinya Maeda; Hyoungseop Kim; Joo Kooi Tan; Seiji Ishikawa; Seiichi Murakami; Takatoshi Aoki

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자료유형: 학술저널

저자정보: Takumi Tokisa Noriaki Miyake (Kyushu Institute of Technology) Shinya Maeda (Kyushu Institute of Technology) Hyoungseop Kim (Kyushu Institute of Technology) Joo Kooi Tan (Kyushu Institute of Technology) Seiji Ishikawa (Kyushu Institute of Technology) Seiichi Murakami (University of Occupational & Environmental Health) Takatoshi Aoki (University of Occupational & Environmental Health)

저널정보: 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.12 No.2

발행연도: 2012.6

수록면: 137 - 142 (6page)

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The temporal subtraction technique as one of computer aided diagnosis has been introduced in medical fields to enhance the interval changes such as formation of new lesions and changes in existing abnormalities on deference image. With the temporal subtraction technique radiologists can easily detect lung nodules on visual screening. Until now, two-dimensional temporal subtraction imaging technique has been introduced for the clinical test. We have developed new temporal subtraction method to remove the subtraction artifacts which is caused by mis-registration on temporal subtraction images of lungs on MDCT images. In this paper, we propose a new computer aided diagnosis scheme for automatic enhancing the lung nodules from the temporal subtraction of thoracic MDCT images. At first, the candidates regions included nodules are detected by the multiple threshold technique in terms of the pixel value on the temporal subtraction images. Then, a rule-base method and artificial neural networks is utilized to remove the false positives of nodule candidates which is obtained temporal subtraction images. We have applied our detection of lung nodules to 30 thoracic MDCT image sets including lung nodules. With the detection method, satisfactory experimental results are obtained. Some experimental results are shown with discussion.

#Lung Nodule #Computer Aided Diagnosis #Temporal Subtraction Technique #Statistical Features #Class-featuring information compression

참고문헌 (17)

참고문헌 신청

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