Neural network based denoised methods for retinal fundus images and MRI brain images

Toufique Ahmed Soomro, Junbin Gao

Research output: Book chapter/Published conference paperConference paperpeer-review

5 Citations (Scopus)


Image processing is an active research area in which medical image processing is a highly challenging field. Medical imaging techniques are used to image the inner portion of human body for medical diagnosis. In this research work, retinal colour fundus images and MRI brain images noise level has been improved. Fundus Fluorescein Angiography (FFA) is the invasive based technique used to give high contrast retinal images but it used contrast injection and other side Magnetic Resonance Imaging (MRI) is a medical used to produce the high contrast image. The biomedical images are mostly suffered from the varied contrast and due to varied contrast, the details of images are not observed properly even after the image enhancement techniques because the presence of noise. In this research, The High-Resolution Fundus (HRF) database is used and it contained 36 images of two pairs (18 good quality images and 18 bad quality images). Oasis MRI brain image database is also used and it contained 30 images. Radial Basis Function (RBF) neural network gave highest PSNR improvement of 53% and 56% in HRF retinal images database and Oasis MRI Brain images database as compared to wavelet technique (18%,35%) and sub space method(29%,9%). The optimal denoised method is one important step to get better result of contrast normalisation techniques and give accurate results to diagnose the disease progress.
Original languageEnglish
Title of host publicationProceedings of the 2016 International Joint Conference on Neural Networks (IJCNN)
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages7
ISBN (Electronic)9781509006199
Publication statusPublished - 31 Oct 2016
EventIEEE International Joint Conference on Neural Networks: IJCNN 2016 - Vancouver Convention Centre, Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016 (Conference website)


ConferenceIEEE International Joint Conference on Neural Networks
OtherOn behalf of the organizing committee, it is our great pleasure to invite you to the bi-annual IEEE World Congress on Computational Intelligence (IEEE WCCI) which will be held in the magnificent city of Vancouver, Canada, 24-29 July 2016. Financially sponsored by the IEEE Computational Intelligence Society (CIS), IEEE WCCI 2016 will host three conferences: The 2016 International Joint Conference on Neural Networks (IJCNN 2016), the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), and the 2016 IEEE Congress on Evolutionary Computation (IEEE CEC 2016) under one roof.
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