Web-based training for radiologists of breast ultrasound

Xianhai Huang; Lijuan Ling; Qinghua Huang; Yidi Lin; Xingzhang Long; Longzhong Liu

doi:10.1109/CISP-BMEI.2017.8302273

Web-based training for radiologists of breast ultrasound

Xianhai Huang, Lijuan Ling, Qinghua Huang, Yidi Lin, Xingzhang Long, Longzhong Liu

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

2 Scopus citations

Abstract

Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.

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	1-6
Number of pages	6
ISBN (Electronic)	9781538619377
DOIs	https://doi.org/10.1109/CISP-BMEI.2017.8302273
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 ultrasound images
database
feature scoring
training system
web-based

UN SDGs

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

Access to Document

10.1109/CISP-BMEI.2017.8302273

Cite this

Huang, X., Ling, L., Huang, Q., Lin, Y., Long, X., & Liu, L. (2017). Web-based training for radiologists of breast ultrasound. 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. 1-6). (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.2017.8302273

Huang, Xianhai ; Ling, Lijuan ; Huang, Qinghua et al. / Web-based training for radiologists of breast ultrasound. 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. 1-6 (Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017).

@inproceedings{41fd3c34aeb3466488296d418715e219,

title = "Web-based training for radiologists of breast ultrasound",

abstract = "Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.",

keywords = "BI-RADS, breast ultrasound images, database, feature scoring, training system, web-based",

author = "Xianhai Huang and Lijuan Ling and Qinghua Huang and Yidi Lin and Xingzhang Long and Longzhong Liu",

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",

month = jul,

day = "2",

doi = "10.1109/CISP-BMEI.2017.8302273",

language = "英语",

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

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--6",

editor = "Qingli Li and Lipo Wang and Mei Zhou and Li Sun and Song Qiu and Hongying Liu",

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

}

Huang, X, Ling, L, Huang, Q, Lin, Y, Long, X & Liu, L 2017, Web-based training for radiologists of breast ultrasound. 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. 1-6, 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.2017.8302273

Web-based training for radiologists of breast ultrasound. / Huang, Xianhai; Ling, Lijuan; Huang, Qinghua et al.
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. 1-6 (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 - Web-based training for radiologists of breast ultrasound

AU - Huang, Xianhai

AU - Ling, Lijuan

AU - Huang, Qinghua

AU - Lin, Yidi

AU - Long, Xingzhang

AU - Liu, Longzhong

PY - 2017/7/2

Y1 - 2017/7/2

N2 - Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.

AB - Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.

KW - BI-RADS

KW - breast ultrasound images

KW - database

KW - feature scoring

KW - training system

KW - web-based

UR - http://www.scopus.com/inward/record.url?scp=85047468775&partnerID=8YFLogxK

U2 - 10.1109/CISP-BMEI.2017.8302273

DO - 10.1109/CISP-BMEI.2017.8302273

M3 - 会议稿件

AN - SCOPUS:85047468775

T3 - Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017

SP - 1

EP - 6

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

A2 - Li, Qingli

A2 - Wang, Lipo

A2 - Zhou, Mei

A2 - Sun, Li

A2 - Qiu, Song

A2 - Liu, Hongying

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017

Y2 - 14 October 2017 through 16 October 2017

ER -

Huang X, Ling L, Huang Q, Lin Y, Long X, Liu L. Web-based training for radiologists of breast ultrasound. 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. 1-6. (Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017). doi: 10.1109/CISP-BMEI.2017.8302273

Web-based training for radiologists of breast ultrasound

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this