Ultrasonic classification of breast tumors based on multi-instance learning

Jianhua Huang; Cong Hu; Yingtao Zhang; Jiafeng Liu; Xianglong Tang

doi:10.1117/12.900946

5 December 2011 Ultrasonic classification of breast tumors based on multi-instance learning

Jianhua Huang, Cong Hu, Yingtao Zhang, Jiafeng Liu, Xianglong Tang

Proceedings Volume 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing; 80050R (2011) https://doi.org/10.1117/12.900946
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Currently, locating the tumor ROI is the prerequisite of feature extraction. However, due to the low contrast and complex background of ultrasound images it is hard to obtain the accurate tumor ROI. Other organizations often been wrongly extracted as a tumor region, result in multi-ROI (non-tumor, tumor) in one image. As the result, the performance of tumor classification algorithms will be poor. In such case, ability to discriminate non-tumor and tumor area of classifier is of the most important. This paper proposed bag structure constructor on the basis of multi-ROI and multiple instance learning (MIL) classification algorithm is introduced to solve the above problem that has ability to discriminate non-tumor and tumor area to some extent. Experiments show that accuracy of the proposed method in such problems is 10% more than the traditional ultrasonic classification of breast tumor.

Citation Download Citation

Jianhua Huang, Cong Hu, Yingtao Zhang, Jiafeng Liu, and Xianglong Tang "Ultrasonic classification of breast tumors based on multi-instance learning", Proc. SPIE 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing, 80050R (5 December 2011); https://doi.org/10.1117/12.900946

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