A Benchmark for Breast Ultrasound Image Segmentation (BUSIS)

نویسندگان

  • Min Xian
  • Yingtao Zhang
  • Heng-Da Cheng
  • Fei Xu
  • Kuan Huang
  • Boyu Zhang
  • Jianrui Ding
  • Chunping Ning
  • Ying Wang
چکیده

Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Computer-Aided Diagnosis (CAD) systems. Many BUS segmentation approaches have been proposed in the last two decades, but the performances of most approaches have been assessed using relatively small private datasets with differ-ent quantitative metrics, which result in discrepancy in performance comparison. Therefore, there is a pressing need for building a benchmark to compare existing methods using a public dataset objectively, and to determine the performance of the best breast tumor segmentation algorithm available today and to investigate what segmentation strategies are valuable in clinical practice and theoretical study. In this work, we will publish a B-mode BUS image segmentation benchmark (BUSIS) with 562 images and compare the performance of five state-of-the-art BUS segmentation methods quantitatively.

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عنوان ژورنال:
  • CoRR

دوره abs/1801.03182  شماره 

صفحات  -

تاریخ انتشار 2018