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Andrey S. Krylov - IEEE Xplore Author Profile

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Magnetic Resonance Imaging (MRI) plays a major role in the diagnosis of several diseases. However, the acquisition of measurements in the k-space domain, which is the basis for image reconstruction, takes a long time compared to other imaging modalities and is comparatively costly. In this context, undersampled MRI reconstruction is an approach for decreasing the acquisition duration and the exam'...Show More
The most recent 3D object detectors for point clouds rely on the coarse voxel-based representation rather than the accurate point-based representation due to a higher box recall in the voxel-based Region Proposal Network (RPN). However, the detection accuracy is severely restricted by the information loss of pose details in the voxels. Different from considering the point cloud as voxel or point r...Show More
The perceptual quality of stereoscopic images plays an essential role in the human perception of visual information. However, most available stereoscopic image quality assessment (SIQA) methods evaluate 3D visual experience using hand-crafted features or shallow architectures, which cannot model the visual properties of stereo images well. In this paper, we use convolutional neural networks (CNNs)...Show More
The paper addresses the problem of no-reference parameter choice for image denoising by Perona-Malik image diffusion algorithm using two models. The idea of the approach is to analyze the difference image between noisy input image and the outcome of the denoising algorithm for the presence of structured data from the input image. The analysis consists of the calculation of the mutual information -...Show More
The paper proposes an improvement of the grid warping algorithm for solving the edge sharpening problem. The idea of the grid warping is to transform the neighborhood of the edges in order to make the edge transient area thinner. This approach does not amplify the noise and does not introduce ringing artifact. The idea of the improvement is to analyze the curvature of the gradient field at edge po...Show More
Motivated by the success of convolutional neural networks (CNNs) in image-related applications, in this paper, we design an effective method for no-reference 3D image quality assessment (3D IQA) through CNN-based feature extraction and consolidation strategy. In the first and most vital stage, quality-aware features, which reflect the inherent quality of images, are extracted by a fine-tuned CNN m...Show More
An automatic multiscale algorithm for Block-matching and 3D filtering (BM3D) method de noising parameter selection has been proposed. To optimize the filtering parameter the presence of retained structures in the ridge areas is analysed for the difference of the initial noisy and filtered images. Appearance of regular components on method noise is controlled using mutual information. An estimation...Show More
The paper presents a method for linear motion blur and out-of-focus blur suppression in photographic images. Conventional image deconvolution algorithms usually have a regularization parameter that specifies a trade-off between incomplete blur removal and high probability of artifacts like ringing and noise. The idea of the proposed image deblurring method is to apply grid warping approach to impr...Show More
In this work we propose a post-processing method for BM3D algorithm that has become a state-of-the-art image denoising and deblurring algorithm. Although BM3D algorithm produces results with high objective metrics values, it also adds noticeable high-frequency artifacts. We suppress these artifacts using second order Total Generalized Variation (TG V) algorithm. TGV algorithm is an extension of To...Show More
With the booming of 3-D image processing in the entertainment industry and 3-D multimedia applications todays, the technology for assessing the quality of stereoscopic image faces more challenging tasks than its 2-D counterparts, such as binocular combination, stereo matching, and binocular rivalry. In this paper, a novel stereoscopic image quality assessment method is proposed by jointly explorin...Show More
A recent imaging modality Diffusion Tensor Imaging completes information used from Structural MRI in studies of Alzheimer disease. A large number of recent studies has explored pathologic staging of Alzheimer disease using the Mean Diffusivity maps extracted from the Diffusion Tensor Imaging modality. The Deep Neural Networks are seducing tools for classification of subjects' imaging data in compu...Show More
The pervasion of 3-D technologies over the years gives rise to the increasing demands of accurate and efficient stereoscopic image quality assessment (SIQA) methods, designed to automatically supervise and optimize 3-D image and video processing systems. Though 2-D IQA has attracted considerable attention, its 3-D counterpart is yet to be well explored. In this paper, a no-reference SIQA method us...Show More
The amount of image data generated in single particle cryo-electron microscopy (cryo-EM) is huge. This technique is based on the reconstruction of the 3D model of a particle using its 2D projections. The most common way to reduce the noise in particle projection images is averaging. The essential step before the averaging is the alignment of projections. In this work, we propose a fast 2D rigid re...Show More
Numerous algorithms exist for the problem of deconvolution of blurred images. But due to ill-posed nature of deconvolution, many images still remain blurry after deblurring. An edge sharpening algorithm is proposed in the paper to further improve the quality of blurry images in edge areas. The method is based on pixel grid warping, its main idea is to move pixels in the direction of the nearest im...Show More
A new learning model for image resampling with convolutional neural network is proposed. Its main idea is the dataset preparation method for deep learning. The proposed algorithm can work with noisy and noiseless images and provides good quality for wide noise level range. The method was tested using standard datasets and was also applied for retinal image resampling.Show More
A method of enhancing the 3D structure of fundus images has been developed. It is based on grid warping techniques and ensures both denoising and vessel sharpening of fundus images. The method has been tested with phantom translucent 3D object of vessels processed using Tikhonov regularization method.Show More
A new edge-directional image resampling method is proposed. The method uses a weighted sum of two adaptive 4x4 interpolation kernels to construct high-resolution pixels. The weights are chosen according to the local gradient features for each pixel. The interpolation kernels are learned using pairs of low- and high-resolution images taken from LIVE image database. The method has low complexity and...Show More
An analysis of speckle filtering influence on B-mode ultrasound image texture-based determination of the liver fibrosis stage has been performed. We developed a comprehensive method for liver texture analysis based on 10–20 textural characteristics. These characteristics were found as most informative from 1390 textural features calculated using Laws' masks, co-occurrence matrix, gray level run-le...Show More
In this paper, we propose an improved acceleration scheme for the mutual entropy maximization method for biomedical image registration. Our approach is based on fast adaptive bidirectional empirical mode decomposition (FABEMD) and aims to reduce the computational complexity of the mutual entropy maximization algorithm by extracting only information essential for registration. We apply several adap...Show More
In this work we develop a post-processing algorithm which enhances the results of the existing image deblurring methods. It performs additional edge sharpening using grid warping. The idea of the proposed algorithm is to transform the neighborhood of the edge so that the neighboring pixels move closer to the edge, and then resample the image from the warped grid to the original uniform grid. The p...Show More
An approach of including warping algorithms into total variation image enhancement methods is suggested. The idea of warping is to make edges sharper using pixel grid transform so that the pixels near edges move closer to the edges. The advantage of using warping approach is that the change of the total variation value is small, so it can be used to improve the results of total variation image enh...Show More
The problem of non-reference ringing detection is considered. The idea of the proposed method is to decompose the input edges into the sums of blurred edge, ringing oscillations and the residual using sparse representation approach with the pre-generated dictionary. Edges with ringing effect are modeled by applying ideal low-pass filter to the step edge with different cut-off frequencies. Then the...Show More
A new method for image sharpening via image warping is proposed. The idea of the method is to warp the uniform grid of the image in a way that the pixels around the blurred edge move closer to the edge according to its blurriness. The advantage of the proposed method is that instead of an accurate estimation of the blur kernel only approximate value of the edge blur level is required. Also, since ...Show More
The paper addresses the problem of retinal image quality assessment, in particular the problem of blur detection for retinal images is considered. The blur value is obtained using an analysis of blood vessel edge widths as the vasculature is the object that is least prone to structural distortion even if blurred. The paper presents the model of a general edge based on the Gaussian filtering and al...Show More
Two problems of text images enhancement are considered in the paper: superresolution and deringing. The problem of superresolution is the reconstruction of a high resolution image from several low resolution observations. Regularization method with bilateral total variation stabilizer and bimodal penalty function are used to perform the superresolution. Enhancement of text images which includes de...Show More