Observer study of a noise suppression algorithm for computed radiography images

Couwenhoven, Mary; Sehnert, William J.; Wang, Xiaohui; Dupin, Michael; Wandtke, John C.; Don, Steven; Kraus, Richard A.; Paul, Narinder; Halin, Neil J.; Sarno, Robert C.

doi:10.1117/12.595159

Cited by 8 publications

(9 citation statements)

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“…A simplified variation of these approaches, that uses only the intensity of the coefficients obtained in the multi-scale image decomposition instead of their correlation, was used as a denoising step of medical image enhancement algorithm in [8]. Image decomposition to low-frequency and high-frequency components, and subsequent high-frequency component value manipulation was proposed in [2]. An approach that uses similarity between neighborhood of a voxel to evaluate its contribution in the denoising process of volumetric images was proposed in [9].…”

Section: This Paper Is a Revised And Expanded Version Of The Paper Prmentioning

confidence: 99%

“…where is the iteration, is the same as in (2).Coefficients , , , , correspond to the intensity difference between the central pixel , and the neighboring pixel in the recursive neighbor image:…”

Section: Recursive Anisotropic Diffusionmentioning

confidence: 99%

“…[18]. image quality [2]. As can be deduced from the previous statements, noise should be reduced in radiography images to achieve a better image quality, and this should be done as a pre-processing step relative to image enhancement.…”

Section: Introductionmentioning

confidence: 99%

“…Radiation dose reduction is possible with modern high dynamic range detectors that allow a wide range of exposure levels while still producing good contrast images [2]. A negative effect of the radiation reduction strategy is the involuntary increase of the quantum noise level which manifests through a negative effect on image quality.…”

Section: Introductionmentioning

confidence: 99%

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Recursive noise reduction for digital radiography images

Ostojić¹,

Starčević²,

Petrović³

2018

Telfor J

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Abstract-Modern digital radiography images are large, suggesting that a denoising algorithm should be computationally efficient. In this paper, we propose a homomorphic recursive noise reduction approach. The proposed method was compared to anisotropic diffusion on a database consisting of 47 clinical radiography images, and was subjectively deemed better at noise reduction. The proposed approach was shown to require 50 % fewer iterations to produce subjectively the same results. Objective comparison of the algorithms through a structural similarity index and peak signal-to-noise ratio showed that the proposed method outperforms anisotropic diffusion for various signal-to-noise ratios.Index Terms-digital radiography, homomorphic filtering, image noise reduction, recursive filtering.

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Section: This Paper Is a Revised And Expanded Version Of The Paper Prmentioning

confidence: 99%

Section: Recursive Anisotropic Diffusionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Recursive noise reduction for digital radiography images

Ostojić¹,

Starčević²,

Petrović³

2018

Telfor J

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show abstract

“…Image noise with digital images is higher in areas of lower detector dose, e.g., the mediastinum. Since this noise may be perceived as disturbing, special processing algorithms have been developed for CR images to suppress noise in bright (underexposed) image areas [31]. In mammography, such Fig.…”

Section: Digital Mammography Systemsmentioning

confidence: 99%