• Corpus ID: 16571920

Analysis Of Various Quality Metrics for Medical Image Processing

@inproceedings{Kumar2012AnalysisOV,
  title={Analysis Of Various Quality Metrics for Medical Image Processing},
  author={Ravi Kumar and Munish Rattan},
  year={2012}
}
Abstract—This paper presents the comparative analysis of various quality metrics for medical image processing. Measurement of image quality is important for many image processing applications. Image quality assessment is closely related to image similarity assessment in which quality is based on the differences (or similarity) between a degraded image and the original, unmodified image. Objective methods have been used for expressing the image quality because these are automatic and… 

Tables from this paper

Subjective Versus Objective Assessment for Magnetic Resonance Images
TLDR
A database of 210 MR images which contains ten reference images and 200 distorted images is presented and it is shown that the DMOS values are close to the objective FR-IQA metrics.
Review of medical image quality assessment
Analysis of Wavelet Transform for Image Denoising with MSE
TLDR
The method adopted in this report to reconstruct an image from a noisy image is by far the best technique encountered till now and the value of PSNR calculated by this technique is the highest obtained till now.
Efficient representation of texture details in medical images by fusion of Ripplet and DDCT transformed images
TLDR
The transformation of images using Ripplet followed by DDCT ensures a more efficient method for the representation of images with preservation of its fine details like edges and textures.
Image Restoration using Hybrid Super Resolution Error Model
TLDR
A hybrid model has been proposed and implemented that provides the above said features by defining Gaussian and Laplacian noise models for the medical images, so that better image quality can be achieved.
A Comparative Analysis of Various Segmentation Techniques on Dental Images
TLDR
An exhaustive survey of four widely used segmentation techniques has been carried out and the performance comparison of each method within Edge detection, Thresholding, Deformable model and Clustering segmentation technique is provided.
Comparison of Image Quality Measurements in Threshold Determination of Most Popular Gradient Based Edge Detection Algorithms Based on Particle Swarm Optimization
TLDR
The threshold values of the gradient based edge detection algorithms for Roberts, Sobel, Prewitt were determined using the Particle Swarm Optimization (PSO) algorithm, based on the image quality measurements, Mean Squared Error, Peak Signal-to-Noise Ratio, Structural Similarity Index Metrics and Correlation Coefficients.
...
...

References

SHOWING 1-10 OF 15 REFERENCES
A New Method to Remove Noise in Magnetic Resonance and Ultrasound Images
TLDR
In the proposed method median filter is modified by adding more features, and the quality of the output images is measured by the statistical quantity measures: peak signal-to-noise ratio (PSNR), signal- to-no noise ratio (SNR) and root mean square error (RMSE).
Image quality assessment: from error visibility to structural similarity
TLDR
A structural similarity index is developed and its promise is demonstrated through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000.
A universal image quality index
TLDR
Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Structural Similarity Quality Metrics in a Coding Context: Exploring the Space of Realistic Distortions
TLDR
This work evaluates SSIM metrics and proposes a perceptually weighted multiscale variant of SSIM, which introduces a viewing distance dependence and provides a natural way to unify the structural similarity approach with the traditional JND-based perceptual approaches.
Contrast in complex images.
  • E. Peli
  • Physics
    Journal of the Optical Society of America. A, Optics and image science
  • 1990
TLDR
A definition of local band-limited contrast in images is proposed that assigns a contrast value to every point in the image as a function of the spatial frequency band and is helpful in understanding the effects of image-processing algorithms on the perceived contrast.
41 OBJECTIVE VIDEO QUALITY ASSESSMENT
TLDR
It is imperative for a video service system to be able to realize and quantify the video quality degradations that occur in the system, so that it can maintain, control and possibly enhance the quality of the video data.
OBJECTIVE VIDEO QUALITY ASSESSMENT
TLDR
It is imperative for a video service system to be able to realize and quantify the video quality degradations that occur in the system, so that it can maintain, control and possibly enhance the quality of the video data.
Digital image processing using MATLAB
TLDR
1. Fundamentals of Image Processing, 2. Intensity Transformations and Spatial Filtering, and 3. Frequency Domain Processing.
Enhancement of Aerial and Medical Image using Multi resolution pyramid
4 Abstract— Image enhancement has been an area of active research for decades. Most of the studies are aimed at improving the quality of image for better visualization. An approach for contrast
...
...