Login / Signup

Lesion segmentation in breast ultrasound images using the optimized marked watershed method.

Xiaoyan ShenHe MaRuibo LiuHong LiJiachuan HeXinran Wu
Published in: Biomedical engineering online (2021)
The proposed method consists of two steps. In the first step, contrast limited adaptive histogram equalization (CLAHE) and a side window filter (SWF) are used to preprocess BUS images. Lesion contours can be effectively highlighted, and the influence of noise can be eliminated to a great extent. In the second step, we propose adaptive morphological snake (AMS). It can adjust the working parameters adaptively according to the size of the lesion. Its segmentation results are combined with those of the morphological method. Then, we determine the marked area and obtain candidate contours with a marked watershed (MW). Finally, the best lesion contour is chosen by the maximum average radial derivative (ARD).
Keyphrases
  • deep learning
  • convolutional neural network
  • magnetic resonance imaging
  • optical coherence tomography
  • magnetic resonance
  • contrast enhanced
  • ultrasound guided
  • diffusion weighted imaging
  • diffusion weighted