Accelerating volume rendering by ray leaping with back steps

Çelebi, Ömer Cengiz; Çevik, Ulus

doi:10.1016/j.cmpb.2009.05.007

Cited by 4 publications

(2 citation statements)

References 41 publications

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“…For example, an image with a PSNR value of 25 dB may look better than another image with a PSNR value of 35 dB. The corresponding PSNR metric for acceptable images for use in digital radiology varies from 40 dB to 50 dB depending on the metric used [36]. In comparing an original picture and a coded picture, the PSNR figures typically range from +25 to +35 dB [37].…”

Section: The Comparisonsmentioning

confidence: 99%

An Efficient Noisy Pixels Detection Model for CT Images using Extreme Learning Machines

Çalışkan

Çevik

2018

Teh. vjesn.

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In this study, a new and rapid hidden resource decomposition method has been proposed to determine noisy pixels by adopting the extreme learning machines (ELM) method. The goal of this method is not only to determine noisy pixels, but also to protect critical structural information that can be used for disease diagnosis. In order to facilitate the diagnosis and also the treatment of patients in medicine, two-dimensional (2-D) images were calculated tomography (CT) which is obtained using medical imaging techniques. Utilizing a large number of CT images, promising results have been obtained from these experiments. The proposed method has shown a significant improvement on mean squared error and peak signal-to-noise ratio. The experimental results indicate that the proposed method is statistically efficient, and it has a good performance with a high learning speed. In the experiments, the results demonstrated that remarkable successive rates were obtained through the ELM method.

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Section: The Comparisonsmentioning

confidence: 99%

An Efficient Noisy Pixels Detection Model for CT Images using Extreme Learning Machines

Çalışkan

Çevik

2018

Teh. vjesn.

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“…This method is called the stepping technique. Intensity values are sampled at evenly spaced intervals along the ray by trilinear interpolation of the surrounding voxels [5]. Transfer functions are used to map the sampled values to an appropriate color and opacity.…”

Section: Introductionmentioning

confidence: 99%

Neville interpolation-based normal estimation

Özyildirim¹,

Çevik²

2017

Turk J Elec Eng & Comp Sci

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Displaying useful and meaningful information from 3D data is known as volume rendering. Ray casting is one of the most frequently used direct volume rendering methods. It consists of data preparation, sampling, classification, compositing, and shading steps. Normal values are needed for efficient shading. However, 3D volumetric data are discrete and cannot be used directly for shading. Hence, the estimation of normal values, at each voxel on the surface, is needed for realistic shading. In normal estimation, the use of small voxel neighborhoods results in the staircase effect. On the other hand, the use of larger voxel neighborhoods causes loss of details in the final image. In this work, an alternative normal estimation method that uses large voxel neighborhoods is proposed for providing smoother images without losing details.

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The role of real-time in biomedical science: A meta-analysis on computational complexity, delay and speedup

Faust

Acharya

2015

Computers in Biology and Medicine

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Accelerating volume rendering by ray leaping with back steps

Cited by 4 publications

References 41 publications

An Efficient Noisy Pixels Detection Model for CT Images using Extreme Learning Machines

An Efficient Noisy Pixels Detection Model for CT Images using Extreme Learning Machines

Neville interpolation-based normal estimation

The role of real-time in biomedical science: A meta-analysis on computational complexity, delay and speedup

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