The application of BI-RADS feature in the ultrasound breast tumor CAD system

Fan Zhang; Qinghua Huang; Xuelong Li

doi:10.1109/CISP-BMEI.2017.8302276

The application of BI-RADS feature in the ultrasound breast tumor CAD system

Fan Zhang, Qinghua Huang, Xuelong Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The breast cancer is one of the most common diseases in women. This paper proposed a breast tumor computer aided diagnosis (CAD) system utilized the Breast Imaging Reporting and Data System (BI-RADS) features. The BI-RADS feature scoring scheme is designed to transform the BI-RADS report to a vector. And the decision tree algorithm is adopted to classify the vector. Compared with previous CAD system, the proposed system is easier to be understood by the clinician. Without the image preprocessing, the proposed system can be applied in different ultrasound machines. There are 440 samples collected from the Cancer Center of Sun Yat-sen University. In the experiment, the five-fold cross validation is employed to evaluate the proposed system. The result shows that the performance of the proposed system is better than the CAD method which takes the BI-RADS feature as a guide to extract features from images. The average accuracy achieves 89.38%, specificity is 90.74%, sensitivity is 86.18%, positive predictive value (PPV) reaches 93.57% and negative predictive value (NVP) is 79.82%.

Original language	English
Title of host publication	Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
Editors	Qingli Li, Lipo Wang, Mei Zhou, Li Sun, Song Qiu, Hongying Liu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538619377
DOIs	https://doi.org/10.1109/CISP-BMEI.2017.8302276
State	Published - 2 Jul 2017
Externally published	Yes
Event	10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017 - Shanghai, China Duration: 14 Oct 2017 → 16 Oct 2017

Publication series

Name	Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
Volume	2018-January

Conference

Conference	10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
Country/Territory	China
City	Shanghai
Period	14/10/17 → 16/10/17

Keywords

BI-RADS
Breast tumors CAD system
Decision tree

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CISP-BMEI.2017.8302276

Cite this

Zhang, F., Huang, Q., & Li, X. (2017). The application of BI-RADS feature in the ultrasound breast tumor CAD system. In Q. Li, L. Wang, M. Zhou, L. Sun, S. Qiu, & H. Liu (Eds.), Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017 (pp. 1-5). (Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISP-BMEI.2017.8302276

Zhang, Fan ; Huang, Qinghua ; Li, Xuelong. / The application of BI-RADS feature in the ultrasound breast tumor CAD system. Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017. editor / Qingli Li ; Lipo Wang ; Mei Zhou ; Li Sun ; Song Qiu ; Hongying Liu. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-5 (Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017).

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title = "The application of BI-RADS feature in the ultrasound breast tumor CAD system",

abstract = "The breast cancer is one of the most common diseases in women. This paper proposed a breast tumor computer aided diagnosis (CAD) system utilized the Breast Imaging Reporting and Data System (BI-RADS) features. The BI-RADS feature scoring scheme is designed to transform the BI-RADS report to a vector. And the decision tree algorithm is adopted to classify the vector. Compared with previous CAD system, the proposed system is easier to be understood by the clinician. Without the image preprocessing, the proposed system can be applied in different ultrasound machines. There are 440 samples collected from the Cancer Center of Sun Yat-sen University. In the experiment, the five-fold cross validation is employed to evaluate the proposed system. The result shows that the performance of the proposed system is better than the CAD method which takes the BI-RADS feature as a guide to extract features from images. The average accuracy achieves 89.38%, specificity is 90.74%, sensitivity is 86.18%, positive predictive value (PPV) reaches 93.57% and negative predictive value (NVP) is 79.82%.",

keywords = "BI-RADS, Breast tumors CAD system, Decision tree",

author = "Fan Zhang and Qinghua Huang and Xuelong Li",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017 ; Conference date: 14-10-2017 Through 16-10-2017",

year = "2017",

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doi = "10.1109/CISP-BMEI.2017.8302276",

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Zhang, F, Huang, Q & Li, X 2017, The application of BI-RADS feature in the ultrasound breast tumor CAD system. in Q Li, L Wang, M Zhou, L Sun, S Qiu & H Liu (eds), Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017. Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017, Shanghai, China, 14/10/17. https://doi.org/10.1109/CISP-BMEI.2017.8302276

The application of BI-RADS feature in the ultrasound breast tumor CAD system. / Zhang, Fan; Huang, Qinghua; Li, Xuelong.
Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017. ed. / Qingli Li; Lipo Wang; Mei Zhou; Li Sun; Song Qiu; Hongying Liu. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-5 (Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - The application of BI-RADS feature in the ultrasound breast tumor CAD system

AU - Zhang, Fan

AU - Huang, Qinghua

AU - Li, Xuelong

PY - 2017/7/2

Y1 - 2017/7/2

N2 - The breast cancer is one of the most common diseases in women. This paper proposed a breast tumor computer aided diagnosis (CAD) system utilized the Breast Imaging Reporting and Data System (BI-RADS) features. The BI-RADS feature scoring scheme is designed to transform the BI-RADS report to a vector. And the decision tree algorithm is adopted to classify the vector. Compared with previous CAD system, the proposed system is easier to be understood by the clinician. Without the image preprocessing, the proposed system can be applied in different ultrasound machines. There are 440 samples collected from the Cancer Center of Sun Yat-sen University. In the experiment, the five-fold cross validation is employed to evaluate the proposed system. The result shows that the performance of the proposed system is better than the CAD method which takes the BI-RADS feature as a guide to extract features from images. The average accuracy achieves 89.38%, specificity is 90.74%, sensitivity is 86.18%, positive predictive value (PPV) reaches 93.57% and negative predictive value (NVP) is 79.82%.

AB - The breast cancer is one of the most common diseases in women. This paper proposed a breast tumor computer aided diagnosis (CAD) system utilized the Breast Imaging Reporting and Data System (BI-RADS) features. The BI-RADS feature scoring scheme is designed to transform the BI-RADS report to a vector. And the decision tree algorithm is adopted to classify the vector. Compared with previous CAD system, the proposed system is easier to be understood by the clinician. Without the image preprocessing, the proposed system can be applied in different ultrasound machines. There are 440 samples collected from the Cancer Center of Sun Yat-sen University. In the experiment, the five-fold cross validation is employed to evaluate the proposed system. The result shows that the performance of the proposed system is better than the CAD method which takes the BI-RADS feature as a guide to extract features from images. The average accuracy achieves 89.38%, specificity is 90.74%, sensitivity is 86.18%, positive predictive value (PPV) reaches 93.57% and negative predictive value (NVP) is 79.82%.

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BT - Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017

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Zhang F, Huang Q, Li X. The application of BI-RADS feature in the ultrasound breast tumor CAD system. In Li Q, Wang L, Zhou M, Sun L, Qiu S, Liu H, editors, Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-5. (Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017). doi: 10.1109/CISP-BMEI.2017.8302276

The application of BI-RADS feature in the ultrasound breast tumor CAD system

Abstract

Publication series

Conference

Keywords

UN SDGs

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