An Improved Denoising of Medical Images Based on Hybrid Filter Approach and Assess Quality Metrics

Author:

Suneetha Mopidevi1,Subbarao Mopidevi2

Affiliation:

1. GRIET

2. VFSTR

Abstract

Degradation of images and segmentation are the two most demanding fields for medical image processing, particularly when explicitly applied. The involvement of noise not only deteriorates the visual quality but also the precision of the segmentation which is vital to the medical diagnosis process of development. The complicated and monotonous main task is to manually denoise medical images such as CT, ultrasound and large numbers of clinical routine MRI images. The medical image must be denoised automatically. The proposed approach is associated with less complexity, this follows from the fact that, the design of system and time for optimization. Results show their efficacy for noise removal in medical ultrasound and MRI images .The final results of the proposed scheme in terms of noise reduction and structural preservation are excellent. However the proposed scheme is compared with existing methods and the performance of the proposed method in terms of visual quality, image quality index, peak SNR and PSNR is shown to be superior to existing methods.

Publisher

Trans Tech Publications, Ltd.

Subject

General Medicine

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Implementation of Convolutional Neural Network for COVID19 Screening using X-Rays Images;2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE);2023-02-16

2. A Review of Noise Reduction Filtering Techniques for MRI Images;2022 5th International Conference on Contemporary Computing and Informatics (IC3I);2022-12-14

3. Classification And Segmentation Of Brain Tumor Using PNN and CNN;2022 International Conference on Electronics and Renewable Systems (ICEARS);2022-03-16

4. A Novel Medical Image De-noising Algorithm for Efficient Diagnosis in Smart Health Environment;2022 Global Conference on Wireless and Optical Technologies (GCWOT);2022-02-14

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