Automatic detection of malignant tumors on mammogram

H. Kobatake; Y. Yoshinaga; M. Murakami

doi:10.1109/ICIP.1994.413345

Automatic detection of malignant tumors on mammogram

H. Kobatake, Y. Yoshinaga, M. Murakami

Research output: Contribution to journal › Conference article › peer-review

16 Citations (Scopus)

Abstract

The automated detection system consists of two processing steps. The first processing is to enhance cancerous tumors. For the purpose, the adaptive iris filter has been developed, which can enhance only rounded opacities and is insensitive to long and slender shadows. The second one is to discriminate between malignant tumors and the others by applying shape analysis to the tumor candidates. Nine feature parameters have been developed for reliable identification of malignant tumors. Experiments to test the performance of the proposed system have been made. The average number of false positives per image is only 0.18 where the true positive detection rate is 100%. These experimental results have shown the effectiveness of the proposed system.

Original language	English
Article number	413345
Pages (from-to)	407-410
Number of pages	4
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	1
DOIs	https://doi.org/10.1109/ICIP.1994.413345
Publication status	Published - Jan 1 1994
Externally published	Yes
Event	Proceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA Duration: Nov 13 1994 → Nov 16 1994

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.1994.413345

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abstract = "The automated detection system consists of two processing steps. The first processing is to enhance cancerous tumors. For the purpose, the adaptive iris filter has been developed, which can enhance only rounded opacities and is insensitive to long and slender shadows. The second one is to discriminate between malignant tumors and the others by applying shape analysis to the tumor candidates. Nine feature parameters have been developed for reliable identification of malignant tumors. Experiments to test the performance of the proposed system have been made. The average number of false positives per image is only 0.18 where the true positive detection rate is 100%. These experimental results have shown the effectiveness of the proposed system.",

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AU - Kobatake, H.

AU - Yoshinaga, Y.

AU - Murakami, M.

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N2 - The automated detection system consists of two processing steps. The first processing is to enhance cancerous tumors. For the purpose, the adaptive iris filter has been developed, which can enhance only rounded opacities and is insensitive to long and slender shadows. The second one is to discriminate between malignant tumors and the others by applying shape analysis to the tumor candidates. Nine feature parameters have been developed for reliable identification of malignant tumors. Experiments to test the performance of the proposed system have been made. The average number of false positives per image is only 0.18 where the true positive detection rate is 100%. These experimental results have shown the effectiveness of the proposed system.

AB - The automated detection system consists of two processing steps. The first processing is to enhance cancerous tumors. For the purpose, the adaptive iris filter has been developed, which can enhance only rounded opacities and is insensitive to long and slender shadows. The second one is to discriminate between malignant tumors and the others by applying shape analysis to the tumor candidates. Nine feature parameters have been developed for reliable identification of malignant tumors. Experiments to test the performance of the proposed system have been made. The average number of false positives per image is only 0.18 where the true positive detection rate is 100%. These experimental results have shown the effectiveness of the proposed system.

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