HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

A Novel Approach for Medical Images Noise Reduction Using Neural Filter

Abstract : This paper is dedicated to the presentation of a new denoising method for medical images. In the proposed approach, a neural filter is designed based on total variation regularization using a multilayer neural network (MLP) to reduce the noise from the degraded images. To train the network we use optimization techniques, which require the calculation of the gradient of the error to adjust the weights by the minimization of an appropriate error function. The new approach is based on taking profit from local information (neighborhood) of the pixel to denoise it. The proposed method can restore degraded images and preserves the discontinuities. The considered filter was used to reduce noise from X-ray and MRI medical images giving good results when compared to other approaches.
Document type :
Conference papers
Complete list of metadata

Contributor : Frédéric Davesne Connect in order to contact the contributor
Submitted on : Wednesday, April 25, 2018 - 3:40:21 PM
Last modification on : Saturday, May 1, 2021 - 3:40:59 AM


  • HAL Id : hal-01778328, version 1


Mohammed Debakla, Khalifa Djemal, Mohamed Benyettou. A Novel Approach for Medical Images Noise Reduction Using Neural Filter. 2nd global conference on computer science, software, networks and engineering (COMENG 2014), Nov 2014, Izmir, Kusadasi, Turkey. ⟨hal-01778328⟩



Record views