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Breast Tumor Detection in Ultrasound Images Using Deep Learning

  • Zhantao CaoEmail author
  • Lixin Duan
  • Guowu Yang
  • Ting Yue
  • Qin Chen
  • Huazhu Fu
  • Yanwu Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10530)

Abstract

Detecting tumor regions in breast ultrasound images has always been an interesting topic. Due to the complex structure of breasts and the existence of noise in the ultrasound images, traditional handcraft feature based methods usually cannot achieve satisfactory results. With the recent advance of deep learning, the performance of object detection has been boosted to a great extent, especially for general object detection. In this paper, we aim to systematically evaluate the performance of several existing state-of-the-art object detection methods for breast tumor detection. To achieve that, we have collected a new dataset consisting of 579 benign and 464 malignant lesion cases with the corresponding ultrasound images manually annotated by experienced clinicians. Comprehensive experimental results clearly show that the recently proposed convolutional neural network based method, Single Shot MultiBox Detector (SSD), outperforms other methods in terms of both precision and recall.

Keywords

Deep learning Breast tumor detection 

Notes

Acknowledgement

This work is supported by grants from the National Natural Science Foundation of China (61572109) and the Fundamental Research Funds for the Central Universities (ZYGX2016J164).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Zhantao Cao
    • 1
    Email author
  • Lixin Duan
    • 1
  • Guowu Yang
    • 1
  • Ting Yue
    • 2
  • Qin Chen
    • 3
  • Huazhu Fu
    • 4
  • Yanwu Xu
    • 5
  1. 1.The Big Data Research CenterUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
  3. 3.Sichuan Academy of Medical Sciences and Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduChina
  4. 4.Agency for ScienceTechnology and ResearchSingaporeSingapore
  5. 5.Guangzhou Shiyuan Electronics Co., Ltd.GuangzhouChina

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