3.8 Proceedings Paper

Speckle Noise Removal in Ultrasound Images Using a Deep Convolutional Neural Network and a Specially Designed Loss Function

Journal

MULTISCALE MULTIMODAL MEDICAL IMAGING, MMMI 2019
Volume 11977, Issue -, Pages 85-92

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-030-37969-8_11

Keywords

Ultrasound images; Speckle noise removal; Deep neural networks

Funding

  1. National Key Research and Development Program of China [2018YFC0910700]
  2. National Natural Science Foundation of China [11701018, 11831002, 81801778]

Ask authors/readers for more resources

The removal of speckle noise in ultrasound images has been the focus of a number of researches. Meanwhile, deep convolutional neural networks (DCNN) has been proved effective for various computer vision tasks, including image classification, segmentation and denoising. In this paper, we apply deep convolutional neural network to remove speckle noise in ultrasound images. Besides, a new hybrid loss function is specially designed for speckle noise removal, which can result in faster and more stable convergence during training. Experiments on synthetic and real Ultrasound images show that the proposed model outperforms other speckle reduction methods.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

3.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available