Adaptive orthogonal directional total variation with kernel regression for CT image denoising.

BACKGROUND: Low-dose computed tomography (CT) has been successful in reducing radiation exposure for patients. However, the use of reconstructions from sparse angle sampling in low-dose CT often leads to severe streak artifacts in the reconstructed images. OBJECTIVE: In order to address this issue and preserve image edge details, this study proposes an adaptive orthogonal directional total variation method with kernel regression. METHODS: The CT reconstructed images are initially processed through kernel regression to obtain the N-term Taylor series, which serves as a local representation of the regression function. By expanding the series to the second order, we obtain the desired estimate of the regression function and localized information on the first and second derivatives. To mitigate the noise impact on these derivatives, kernel regression is performed again to update the first and second derivatives. Subsequently, the original reconstructed image, its local approximation, and the updated derivatives are summed using a weighting scheme to derive the image used for calculating orientation information. For further removal of stripe artifacts, the study introduces the adaptive orthogonal directional total variation (AODTV) method, which denoises along both the edge direction and the normal direction, guided by the previously obtained orientation. RESULTS: Both simulation and real experiments have obtained good results. The results of two real experiments show that the proposed method has obtained PSNR values of 34.5408 dB and 29.4634 dB, which are 1.2392-5.9333 dB and 2.828-6.7995 dB higher than the contrast denoising algorithm, respectively, indicating that the proposed method has good denoising performance. CONCLUSIONS: The study demonstrates the effectiveness of the method in eliminating strip artifacts and preserving the fine details of the images.

Truncated total variation in fractional B-spline wavelet transform for micro-CT image denoising.

BACKGROUND: In medical applications, computed tomography (CT) is widely used to evaluate various sample characteristics. However, image quality of CT reconstruction can be degraded due to artifacts. OBJECTIVE: To propose and test a truncated total variation (truncation TV) model to solve the problem of large penalties for the total variation (TV) model. METHODS: In this study, a truncated TV image denoising model in the fractional B-spline wavelet domain is developed to obtain the best solution. The method is validated by the analysis of CT reconstructed images of actual biological Pigeons samples. For this purpose, several indices including the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) and mean square error (MSE) are used to evaluate the quality of images. RESULTS: Comparing to the conventional truncated TV model that yields 22.55, 0.688 and 361.17 in PSNR, SSIM and MSE, respectively, using the proposed fractional B-spline-truncated TV model, the computed values of these evaluation indices change to 24.24, 0.898 and 244.98, respectively, indicating substantial reduction of image noise with higher PSNR and SSIM, and lower MSE. CONCLUSIONS: Study results demonstrate that compared with many classic image denoising methods, the new denoising algorithm proposed in this study can more effectively suppresses the reconstructed CT image artifacts while maintaining the detailed image structure.

Delayed Dural Arteriovenous Fistula at the Transverse-Sigmoid Sinus Secondary to Petroclival Meningioma Surgery Via Far Lateral Approach.

Intracranial dural arteriovenous fistulas (DAVFs) are typified by pathological anastomoses between meningeal arteries and dural venous sinuses or cortical veins. There are many causes contributing to the etiology of DAVFs. Among the variable causes, acquired DAVFs secondary to craniotomy had rarely been reported, especially for delayed DAVFs at the transverse-sigmoid sinus. Till now, there are only 12 published cases of delayed DAVFs at the transverse-sigmoid sinus secondary to craniotomy. Herein, the authors describe such an extraordinary rare case secondary to petroclival meningioma resection via far lateral approach, and to the best knowledge of us, this is the first well-documented case of delayed DAVF at the transverse-sigmoid sinus following far lateral craniotomy. Furthermore, cases of delayed DAVFs at the transverse-sigmoid sinus secondary to craniotomy were reviewed and investigated, and the clinical characteristics and treatment were also broadly discussed.

Aneurysms Arising From the Fenestrated Middle Cerebral Artery.

Intracranial artery fenestration is segmental duplication of the lumen into 2 distinct channels and is known to have a low angiographical incidence of 0.3 to 0.9%. Intracranial artery fenestration is frequently associated with aneurysms, and aneurysms arising at the site of fenestrated middle cerebral artery (MCA) is extremely rare. To our best knowledge, there are only 10 such patients have been reported. Herein, the authors describe the 11th case of aneurysm arising from the fenestrated MCA. As the characteristics of fenestrated MCA aneurysms has not been well determined until now, these interesting patients are investigated and summarized.