NDLI: Efficient medical image enhancement based on CNN-FBB model

Content Provider	IET Digital Library
Author	Qiu, Tao Wen, Chang Xie, Kai Wen, Fang Qing Sheng, Guan Qun Tang, Xin Gong
Abstract	Medical image quality requirements have been increasingly stringent with the recent developments of medical technology. To meet clinical diagnosis needs, an effective medical image enhancement method based on convolutional neural networks (CNNs) and frequency band broadening (FBB) is proposed. Curvelet transform is used to deal with medical data by obtaining the curvelet coefficient in each scale and direction, and the generalised cross-validation is implemented to select the optimal threshold for performing denoising processing. Meanwhile, the cycle spinning scheme is used to wipe off the visible ringing effects along the edges of medical images. Then, FBB and a new CNN model based on the retinex model are used to improve the processed image resolution. Eventually, pixel-level fusion is made between two enhanced medical images from CNN and FBB. In the authors’ study, 50 groups of medical magnetic resonance imaging, X-ray, and computed tomography images in total have been studied. The experimental results indicate that the final enhanced image using the proposed method outperforms other methods. The resolution and the edge details of the processed image are significantly enhanced, providing a more effective and accurate basis for medical workers to diagnose diseases.
Starting Page	1736
Ending Page	1744
Page Count	9
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 10, Aug (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6380
Journal	IET Image Processing
Publisher Date	2019-06-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biology And Medical Computing Biomedical Imaging/measurement Biomedical Magnetic Resonance Imaging Biomedical MRI Clinical Diagnosis CNN-FBB Model Computed Tomography Image Computer Vision And Image Processing Technique Computerised Tomography Convolutional Neural Nets Convolutional Neural Network Curvelet Coefficient Curvelet Transform Curvelet Transforms Cycle Spinning Scheme Denoising Processing Diseases Efficient Medical Image Enhancement Frequency Band Broadening Function Theory And Analysis Image Denoising Image Enhancement Image Fusion Image Resolution Integral Transforms Medical Data Medical Image Enhancement Medical Image Processing Medical Image Quality Medical Magnetic Resonance Imaging Medical Magnetic Resonance Imaging And Spectroscopy Medical Technology Neural Computing Technique Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Radiography And Computed Tomography Retinex Model Spectroscopy Visible Ringing Effect X-Ray Image X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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