An Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism
Department of Biomedical Engineering, Sichuan University, Chengdu 610065, China
*
Author to whom correspondence should be addressed.
Academic Editors: Xiaoning Jiang and Chao Zhang
Sensors 2017, 17(5), 1101; https://doi.org/10.3390/s17051101
Received: 7 March 2017
/
Revised: 6 May 2017
/
Accepted: 7 May 2017
/
Published: 11 May 2017
(This article belongs to the Special Issue Acoustic Sensing and Ultrasonic Drug Delivery)
Human visual mechanisms (HVMs) can quickly localize the most salient object in natural images, but it is ineffective at localizing tumors in ultrasound breast images. In this paper, we research the characteristics of tumors, develop a classic HVM and propose a novel auto-localization method. Comparing to surrounding areas, tumors have higher global and local contrast. In this method, intensity, blackness ratio and superpixel contrast features are combined to compute a saliency map, in which a Winner Take All algorithm is used to localize the most salient region, which is represented by a circle. The results show that the proposed method can successfully avoid the interference caused by background areas of low echo and high intensity. The method has been tested on 400 ultrasound breast images, among which 376 images succeed in localization. This means this method has a high accuracy of 94.00%, indicating its good performance in real-life applications.
View Full-Text
Keywords:
automatic localization; human visual mechanisms; superpixel contrast feature; ultrasound breast tumor
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
-
Externally hosted supplementary file 1
Doi: 10.3969/j.issn.1003-9775.2012.05.013
Link: http://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFD2012&filename=JSJF201205014&uid=WEEvREcwSlJHSldRa1FhdkJkcGkyR0xOakRsdmFpMUFzU0tTVWZ4YTJ6dz0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4ggI8Fm4gTkoUKaID8j8gFw!!&v=MjE2MzRxVHJXTTFGckNVUkwyZll1Wm1GeTds
MDPI and ACS Style
Xie, Y.; Chen, K.; Lin, J. An Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism. Sensors 2017, 17, 1101. https://doi.org/10.3390/s17051101
AMA Style
Xie Y, Chen K, Lin J. An Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism. Sensors. 2017; 17(5):1101. https://doi.org/10.3390/s17051101
Chicago/Turabian StyleXie, Yuting, Ke Chen, and Jiangli Lin. 2017. "An Automatic Localization Algorithm for Ultrasound Breast Tumors Based on Human Visual Mechanism" Sensors 17, no. 5: 1101. https://doi.org/10.3390/s17051101
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
