Detection System of Clustered Microcalcifications on CR Mammogram

Hideya TAKEO; Kazuo SHIMURA; Takashi IMAMURA; Akinobu SHIMIZU; Hidefumi KOBATAKE

doi:10.1093/ietisy/e88-d.11.2591

Detection System of Clustered Microcalcifications on CR Mammogram

Hideya TAKEO, Kazuo SHIMURA, Takashi IMAMURA, Akinobu SHIMIZU, Hidefumi KOBATAKE

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CR (Computed Radiography) is characterized by high sensitivity and wide dynamic range. Moreover, it has the advantage of being able to transfer exposed images directly to a computer-aided detection (CAD) system which is not possible using conventional film digitizer systems. This paper proposes a high-performance clustered microcalcification detection system for CR mammography. Before detecting and classifying candidate regions, the system preprocesses images with a normalization step to take into account various imaging conditions and to enhance microcalcifications with weak contrast. Large-scale experiments using images taken under various imaging conditions at seven hospitals were performed. According to analysis of the experimental results, the proposed system displays high performance. In particular, at a true positive detection rate of 97.1%, the false positive clusters average is only 0.4 per image. The introduction of geometrical features of each microcalcification for identifying true microcalcifications contributed to the performance improvement. One of the aims of this study was to develop a system for practical use. The results indicate that the proposed system is promising.

Publication: IEICE TRANSACTIONS on Information Vol.E88-D No.11 pp.2591-2602

Publication Date: 2005/11/01

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DOI: 10.1093/ietisy/e88-d.11.2591

Type of Manuscript: PAPER

Category: Biological Engineering

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Hideya TAKEO, Kazuo SHIMURA, Takashi IMAMURA, Akinobu SHIMIZU, Hidefumi KOBATAKE, "Detection System of Clustered Microcalcifications on CR Mammogram" in IEICE TRANSACTIONS on Information, vol. E88-D, no. 11, pp. 2591-2602, November 2005, doi: 10.1093/ietisy/e88-d.11.2591.
Abstract: CR (Computed Radiography) is characterized by high sensitivity and wide dynamic range. Moreover, it has the advantage of being able to transfer exposed images directly to a computer-aided detection (CAD) system which is not possible using conventional film digitizer systems. This paper proposes a high-performance clustered microcalcification detection system for CR mammography. Before detecting and classifying candidate regions, the system preprocesses images with a normalization step to take into account various imaging conditions and to enhance microcalcifications with weak contrast. Large-scale experiments using images taken under various imaging conditions at seven hospitals were performed. According to analysis of the experimental results, the proposed system displays high performance. In particular, at a true positive detection rate of 97.1%, the false positive clusters average is only 0.4 per image. The introduction of geometrical features of each microcalcification for identifying true microcalcifications contributed to the performance improvement. One of the aims of this study was to develop a system for practical use. The results indicate that the proposed system is promising.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.11.2591/_p

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@ARTICLE{e88-d_11_2591,
author={Hideya TAKEO, Kazuo SHIMURA, Takashi IMAMURA, Akinobu SHIMIZU, Hidefumi KOBATAKE, },
journal={IEICE TRANSACTIONS on Information},
title={Detection System of Clustered Microcalcifications on CR Mammogram},
year={2005},
volume={E88-D},
number={11},
pages={2591-2602},
abstract={CR (Computed Radiography) is characterized by high sensitivity and wide dynamic range. Moreover, it has the advantage of being able to transfer exposed images directly to a computer-aided detection (CAD) system which is not possible using conventional film digitizer systems. This paper proposes a high-performance clustered microcalcification detection system for CR mammography. Before detecting and classifying candidate regions, the system preprocesses images with a normalization step to take into account various imaging conditions and to enhance microcalcifications with weak contrast. Large-scale experiments using images taken under various imaging conditions at seven hospitals were performed. According to analysis of the experimental results, the proposed system displays high performance. In particular, at a true positive detection rate of 97.1%, the false positive clusters average is only 0.4 per image. The introduction of geometrical features of each microcalcification for identifying true microcalcifications contributed to the performance improvement. One of the aims of this study was to develop a system for practical use. The results indicate that the proposed system is promising.},
keywords={},
doi={10.1093/ietisy/e88-d.11.2591},
ISSN={},
month={November},}

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TY - JOUR
TI - Detection System of Clustered Microcalcifications on CR Mammogram
T2 - IEICE TRANSACTIONS on Information
SP - 2591
EP - 2602
AU - Hideya TAKEO
AU - Kazuo SHIMURA
AU - Takashi IMAMURA
AU - Akinobu SHIMIZU
AU - Hidefumi KOBATAKE
PY - 2005
DO - 10.1093/ietisy/e88-d.11.2591
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2005
AB - CR (Computed Radiography) is characterized by high sensitivity and wide dynamic range. Moreover, it has the advantage of being able to transfer exposed images directly to a computer-aided detection (CAD) system which is not possible using conventional film digitizer systems. This paper proposes a high-performance clustered microcalcification detection system for CR mammography. Before detecting and classifying candidate regions, the system preprocesses images with a normalization step to take into account various imaging conditions and to enhance microcalcifications with weak contrast. Large-scale experiments using images taken under various imaging conditions at seven hospitals were performed. According to analysis of the experimental results, the proposed system displays high performance. In particular, at a true positive detection rate of 97.1%, the false positive clusters average is only 0.4 per image. The introduction of geometrical features of each microcalcification for identifying true microcalcifications contributed to the performance improvement. One of the aims of this study was to develop a system for practical use. The results indicate that the proposed system is promising.
ER -