Surface rendering is a useful method in 3D visualization of brain MR images. Especially when the ... more Surface rendering is a useful method in 3D visualization of brain MR images. Especially when the segmented result of MR images is given in advance, discretized marching cubes (DiscMC) algorithm can be easily utilized. However, the complexity of cerebral surface increases the number of triangles produced by DiscMC and thus, the computation time becomes an impediment to real-time 3D rendering. In order to speed up the 3D rendering, we propose a modified DiscMC table to reduce the number of triangles DiscMC. The proposed method reduces the number of triangles by 30% without loss in brain MR image quality.
Purpose: To reconstruct MR images from subsampled data, we propose a fast reconstruction method u... more Purpose: To reconstruct MR images from subsampled data, we propose a fast reconstruction method using the multilayer perceptron (MLP) algorithm. Methods and materials: We applied MLP to reduce aliasing artifacts generated by subsampling in k-space. The MLP is learned from training data to map aliased input images into desired alias-free images. The input of the MLP is all voxels in the aliased lines of multichannel real and imaginary images from the subsampled k-space data, and the desired output is all voxels in the corresponding alias-free line of the root-sum-of-squares of multichannel images from fully sampled k-space data. Aliasing artifacts in an image reconstructed from subsampled data were reduced by line-by-line processing of the learned MLP architecture. Results: Reconstructed images from the proposed method are better than those from compared methods in terms of normalized root-mean-square error. The proposed method can be applied to image reconstruction for any k-space subsampling patterns in a phase encoding direction. Moreover, to further reduce the reconstruction time, it is easily implemented by parallel processing. We have proposed a reconstruction method using machine learning to accelerate imaging time, which reconstructs high-quality images from subsampled k-space data. It shows flexibility in the use of k-space sampling patterns, and can reconstruct images in real time.
Several lines of evidence indicate verbal abuse (VA) critically impacts the developing brain; how... more Several lines of evidence indicate verbal abuse (VA) critically impacts the developing brain; however, whether VA results in changes in brain neurochemistry has not been established in humans. Here, we hypothesized that exposure to recurrent parental VA elicits heightened glutamate (Glu) responses during the presentation of swear words, which can be measured with functional magnetic resonance spectroscopy (fMRS). During an emotional Stroop task consisting of blocks of color and swear words, metabolite concentration changes were measured in the ventromedial prefrontal cortex (vmPFC) and the left amygdalohippocampal region (AMHC) of healthy adults (14 F/27 M, 23±4 years old) using fMRS. The dynamic changes in Glu and their associations with the emotional state of the participants were finally evaluated based on 36 datasets from the vmPFC and 30 from the AMHC.A repeated-measures analysis of covariance revealed a modest effect of parental VA severity on Glu changes in the vmPFC. Further...
Introduction A reconstruction method was presented by Pruessmann et al. for Sensitivity Encoding ... more Introduction A reconstruction method was presented by Pruessmann et al. for Sensitivity Encoding (SENSE)[1] with arbitrary k-space trajectory [2]. The method can be applied to the MR data acquired on a radial, spiral and random k-space trajectory as well as Cartesian k-space trajectory. However, in the reconstruction procedure, the method requires gridding step which converts the coordinates from arbitrary grid to Cartesian grid. Therefore, it suffers from the gridding interpolation error in the reconstructed image. In this study, we proposed a reconstruction algorithm for parallel imaging with radial k-space trajectory. The presented method does not require gridding step and can reconstruct the images using only magnitude information of the projection data which is obtained after the Fourier transform along the radial direction.
Machine Learning for Medical Image Reconstruction, 2018
Recently, an end-to-end MR image reconstruction technique, called AUTOMAP, was introduced to simp... more Recently, an end-to-end MR image reconstruction technique, called AUTOMAP, was introduced to simplify the complicated reconstruction process of MR image and to improve the quality of reconstructed MR images using deep learning. Despite the benefits of end-to-end architecture and superior quality of reconstructed MR images, AUTOMAP suffers from the large amount of training parameters required by multiple fully connected layers. In this work, we propose a new end-to-end MR image reconstruction technique based on the recurrent neural network (RNN) architecture, which can be more efficiently used for magnetic resonance (MR) image reconstruction than the convolutional neural network (CNN). We modified the RNN architecture of ReNet for image domain data to reconstruct an MR image from k-space data by utilizing recurrent cells. The proposed network reconstructs images from the k-space data with a reduced number of parameters compared with that of fully connected architectures. We present a quantitative evaluation of the proposed method for Cartesian trajectories using nMSE and SSIM. We also present preliminary images reconstructed from k-space data acquired in the radial trajectory.
To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for sing... more To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinat...
2009 16th IEEE International Conference on Image Processing (ICIP), 2009
The H.264/AVC achieves higher coding efficiency than the previous video coding standards such as ... more The H.264/AVC achieves higher coding efficiency than the previous video coding standards such as MPEG-4 and H.263. H.264 adopted the multiple reference-frame motion estimation (MRF-ME). Although this new technique significantly improves the prediction accuracy, it requires very heavy encoding complexity in proportion to the number of reference frames. In this paper, we propose an adaptive reference-frame selection (ARFS) method using neighboring reference-frame information and Bayes theory. We show that the proposed algorithm effectively reduces the encoding complexity of MRF-ME and achieves similar coding gain, compared to the previous methods.
IEEE International Conference on Image Processing 2005, 2005
Down-up sampling of images is an essential process for spatial scalability of the video coding st... more Down-up sampling of images is an essential process for spatial scalability of the video coding standard. We propose an efficient down-up sampling method in spatial domain using DCT kernel. The computational complexity of the proposed method is reduced by taking advantages of various symmetries of the combined DCT kernel. The proposed down-up sampling method is compared to that of MPEG-21 SVM 3.0 [1]. The proposed method outperforms the performance of MPEG-21 SVM 3.0 with slightly increased addition operation.
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001
We have developed a moving-object segmentation method for standard-compliant DCT-based video code... more We have developed a moving-object segmentation method for standard-compliant DCT-based video coder. To be compliant with current block-based video coding standards, the proposed algorithm uses the DCT coefficients and motion vector of a block, respectively, as spatial and temporal features of segmentation. Since block-based motion vector may not be sufficient to represent true motion of object, the proposed algorithm overcomes this problem by using statistical approach. Moreover, the proposed segmentation algorithm operates in parallel with the video coding. Therefore, the proposed segmentation algorithm can be efficiently integrated in parallel with the DCT-based video coder for the improvement of coding efficiency as well as segmentation accuracy.
2006 International Conference on Image Processing, 2006
In this paper, we proposed a new scheme of forming quarterpixel reference of LL band for in-band ... more In this paper, we proposed a new scheme of forming quarterpixel reference of LL band for in-band video coding with spatial scalability. The recently proposed leaky motion compensation and mode-based temporal filtering methods [5] have reduced the drifting error dramatically. However there still remains drifting error because of the use of high quality reference and the difference between high quality and low quality references [5]. In our method, a new reference is formed which gives PSNR higher than the low quality reference. The new reference is used instead of low quality reference in leaky and mode-based methods and experimental results show that improvement can be achieved in PSNR comparison with the existed ones. Index terms-Wavelet transform, video coding, frequency estimation
2006 International Conference on Image Processing, 2006
In a scalable video coding (SVC), spatial up-sampling of video sequences is an important process ... more In a scalable video coding (SVC), spatial up-sampling of video sequences is an important process for spatial scalability. We propose an up-sampling method based on the type-1 DCT. For further improvement of the upsampling method, we introduce an adaptive filtering method, which applies different weighting parameters to DCT coefficients. The proposed adaptive up-sampling method shows much improved PSNR in comparison with the recent H.264 SVC up-sampling method.
A fast motion estimation (ME) algorithm is proposed to search motion vectors for variable blocks.... more A fast motion estimation (ME) algorithm is proposed to search motion vectors for variable blocks. The proposed method is based on the successive elimination algorithm (SEA) using sum norms to find the best estimate of the motion vectors and to implement efficient calculations for variable blocks. The proposed ME algorithm is applied to the Joint Video Team (JVT) encoder that performs a variable-block ME. In terms of computational complexity, the proposed ME algorithm with limited search range searches motion vectors at about 6.3 times as fast as the spiral full search and 5.5 times as fast as the fast full search using the hierarchical sum of absolute difference (SAD), while the PSNR (peak signal-to-noise ratio) of the reconstructed image is slightly degraded with only 0.1~0.4 dB.
A fast block-matching algorithm for motion estimation is described for interframe image coding. U... more A fast block-matching algorithm for motion estimation is described for interframe image coding. Utilizing the fact that the motion is searched by a macroblock basis while the compression is performed by a block basis in many video compression standards, the proposed algorithm produces high PSNR and fast computation while keeping the bit-rate as low as those of conventional fast algorithms. The proposed algorithm uses the subblock sum as a matching parameter and the reversed square sum as a matching criterion. The new matching parameter and criterion reduce the total number of computations for block matching and also keep the quality of the decompressed image. The computational complexity and the compression performance of the proposed algorithm are compared with those of other block-matching algorithms.
IEEE Transactions on Circuits and Systems for Video Technology, 2002
In many image-coding applications such as web browsing, image databases, and telemedicine, it is ... more In many image-coding applications such as web browsing, image databases, and telemedicine, it is useful to reconstruct only a region of interest (ROI) before the rest of the image is reconstructed. In this paper, an ROI coding functionality is incorporated with the set partitioning in hierarchical trees (SPIHT) algorithm for wavelet-based image coding. By placing a higher emphasis on the transform coefficients pertaining to the ROI, the ROI is coded with higher fidelity than the rest of the image in earlier stages of progressive coding. The general thrust of this research is to identify necessary coefficients in wavelet-transform domain for the decoder to reconstruct the desired region. This new method provides better performance than the previously presented methods. Index Terms-Parent of ROI (PROI), progressive transmission, region of interest (ROI) coding, set partitioning in hierarchical trees (SPIHT), wavelet transform.
Surface rendering is a useful method in 3D visualization of brain MR images. Especially when the ... more Surface rendering is a useful method in 3D visualization of brain MR images. Especially when the segmented result of MR images is given in advance, discretized marching cubes (DiscMC) algorithm can be easily utilized. However, the complexity of cerebral surface increases the number of triangles produced by DiscMC and thus, the computation time becomes an impediment to real-time 3D rendering. In order to speed up the 3D rendering, we propose a modified DiscMC table to reduce the number of triangles DiscMC. The proposed method reduces the number of triangles by 30% without loss in brain MR image quality.
Purpose: To reconstruct MR images from subsampled data, we propose a fast reconstruction method u... more Purpose: To reconstruct MR images from subsampled data, we propose a fast reconstruction method using the multilayer perceptron (MLP) algorithm. Methods and materials: We applied MLP to reduce aliasing artifacts generated by subsampling in k-space. The MLP is learned from training data to map aliased input images into desired alias-free images. The input of the MLP is all voxels in the aliased lines of multichannel real and imaginary images from the subsampled k-space data, and the desired output is all voxels in the corresponding alias-free line of the root-sum-of-squares of multichannel images from fully sampled k-space data. Aliasing artifacts in an image reconstructed from subsampled data were reduced by line-by-line processing of the learned MLP architecture. Results: Reconstructed images from the proposed method are better than those from compared methods in terms of normalized root-mean-square error. The proposed method can be applied to image reconstruction for any k-space subsampling patterns in a phase encoding direction. Moreover, to further reduce the reconstruction time, it is easily implemented by parallel processing. We have proposed a reconstruction method using machine learning to accelerate imaging time, which reconstructs high-quality images from subsampled k-space data. It shows flexibility in the use of k-space sampling patterns, and can reconstruct images in real time.
Several lines of evidence indicate verbal abuse (VA) critically impacts the developing brain; how... more Several lines of evidence indicate verbal abuse (VA) critically impacts the developing brain; however, whether VA results in changes in brain neurochemistry has not been established in humans. Here, we hypothesized that exposure to recurrent parental VA elicits heightened glutamate (Glu) responses during the presentation of swear words, which can be measured with functional magnetic resonance spectroscopy (fMRS). During an emotional Stroop task consisting of blocks of color and swear words, metabolite concentration changes were measured in the ventromedial prefrontal cortex (vmPFC) and the left amygdalohippocampal region (AMHC) of healthy adults (14 F/27 M, 23±4 years old) using fMRS. The dynamic changes in Glu and their associations with the emotional state of the participants were finally evaluated based on 36 datasets from the vmPFC and 30 from the AMHC.A repeated-measures analysis of covariance revealed a modest effect of parental VA severity on Glu changes in the vmPFC. Further...
Introduction A reconstruction method was presented by Pruessmann et al. for Sensitivity Encoding ... more Introduction A reconstruction method was presented by Pruessmann et al. for Sensitivity Encoding (SENSE)[1] with arbitrary k-space trajectory [2]. The method can be applied to the MR data acquired on a radial, spiral and random k-space trajectory as well as Cartesian k-space trajectory. However, in the reconstruction procedure, the method requires gridding step which converts the coordinates from arbitrary grid to Cartesian grid. Therefore, it suffers from the gridding interpolation error in the reconstructed image. In this study, we proposed a reconstruction algorithm for parallel imaging with radial k-space trajectory. The presented method does not require gridding step and can reconstruct the images using only magnitude information of the projection data which is obtained after the Fourier transform along the radial direction.
Machine Learning for Medical Image Reconstruction, 2018
Recently, an end-to-end MR image reconstruction technique, called AUTOMAP, was introduced to simp... more Recently, an end-to-end MR image reconstruction technique, called AUTOMAP, was introduced to simplify the complicated reconstruction process of MR image and to improve the quality of reconstructed MR images using deep learning. Despite the benefits of end-to-end architecture and superior quality of reconstructed MR images, AUTOMAP suffers from the large amount of training parameters required by multiple fully connected layers. In this work, we propose a new end-to-end MR image reconstruction technique based on the recurrent neural network (RNN) architecture, which can be more efficiently used for magnetic resonance (MR) image reconstruction than the convolutional neural network (CNN). We modified the RNN architecture of ReNet for image domain data to reconstruct an MR image from k-space data by utilizing recurrent cells. The proposed network reconstructs images from the k-space data with a reduced number of parameters compared with that of fully connected architectures. We present a quantitative evaluation of the proposed method for Cartesian trajectories using nMSE and SSIM. We also present preliminary images reconstructed from k-space data acquired in the radial trajectory.
To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for sing... more To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinat...
2009 16th IEEE International Conference on Image Processing (ICIP), 2009
The H.264/AVC achieves higher coding efficiency than the previous video coding standards such as ... more The H.264/AVC achieves higher coding efficiency than the previous video coding standards such as MPEG-4 and H.263. H.264 adopted the multiple reference-frame motion estimation (MRF-ME). Although this new technique significantly improves the prediction accuracy, it requires very heavy encoding complexity in proportion to the number of reference frames. In this paper, we propose an adaptive reference-frame selection (ARFS) method using neighboring reference-frame information and Bayes theory. We show that the proposed algorithm effectively reduces the encoding complexity of MRF-ME and achieves similar coding gain, compared to the previous methods.
IEEE International Conference on Image Processing 2005, 2005
Down-up sampling of images is an essential process for spatial scalability of the video coding st... more Down-up sampling of images is an essential process for spatial scalability of the video coding standard. We propose an efficient down-up sampling method in spatial domain using DCT kernel. The computational complexity of the proposed method is reduced by taking advantages of various symmetries of the combined DCT kernel. The proposed down-up sampling method is compared to that of MPEG-21 SVM 3.0 [1]. The proposed method outperforms the performance of MPEG-21 SVM 3.0 with slightly increased addition operation.
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001
We have developed a moving-object segmentation method for standard-compliant DCT-based video code... more We have developed a moving-object segmentation method for standard-compliant DCT-based video coder. To be compliant with current block-based video coding standards, the proposed algorithm uses the DCT coefficients and motion vector of a block, respectively, as spatial and temporal features of segmentation. Since block-based motion vector may not be sufficient to represent true motion of object, the proposed algorithm overcomes this problem by using statistical approach. Moreover, the proposed segmentation algorithm operates in parallel with the video coding. Therefore, the proposed segmentation algorithm can be efficiently integrated in parallel with the DCT-based video coder for the improvement of coding efficiency as well as segmentation accuracy.
2006 International Conference on Image Processing, 2006
In this paper, we proposed a new scheme of forming quarterpixel reference of LL band for in-band ... more In this paper, we proposed a new scheme of forming quarterpixel reference of LL band for in-band video coding with spatial scalability. The recently proposed leaky motion compensation and mode-based temporal filtering methods [5] have reduced the drifting error dramatically. However there still remains drifting error because of the use of high quality reference and the difference between high quality and low quality references [5]. In our method, a new reference is formed which gives PSNR higher than the low quality reference. The new reference is used instead of low quality reference in leaky and mode-based methods and experimental results show that improvement can be achieved in PSNR comparison with the existed ones. Index terms-Wavelet transform, video coding, frequency estimation
2006 International Conference on Image Processing, 2006
In a scalable video coding (SVC), spatial up-sampling of video sequences is an important process ... more In a scalable video coding (SVC), spatial up-sampling of video sequences is an important process for spatial scalability. We propose an up-sampling method based on the type-1 DCT. For further improvement of the upsampling method, we introduce an adaptive filtering method, which applies different weighting parameters to DCT coefficients. The proposed adaptive up-sampling method shows much improved PSNR in comparison with the recent H.264 SVC up-sampling method.
A fast motion estimation (ME) algorithm is proposed to search motion vectors for variable blocks.... more A fast motion estimation (ME) algorithm is proposed to search motion vectors for variable blocks. The proposed method is based on the successive elimination algorithm (SEA) using sum norms to find the best estimate of the motion vectors and to implement efficient calculations for variable blocks. The proposed ME algorithm is applied to the Joint Video Team (JVT) encoder that performs a variable-block ME. In terms of computational complexity, the proposed ME algorithm with limited search range searches motion vectors at about 6.3 times as fast as the spiral full search and 5.5 times as fast as the fast full search using the hierarchical sum of absolute difference (SAD), while the PSNR (peak signal-to-noise ratio) of the reconstructed image is slightly degraded with only 0.1~0.4 dB.
A fast block-matching algorithm for motion estimation is described for interframe image coding. U... more A fast block-matching algorithm for motion estimation is described for interframe image coding. Utilizing the fact that the motion is searched by a macroblock basis while the compression is performed by a block basis in many video compression standards, the proposed algorithm produces high PSNR and fast computation while keeping the bit-rate as low as those of conventional fast algorithms. The proposed algorithm uses the subblock sum as a matching parameter and the reversed square sum as a matching criterion. The new matching parameter and criterion reduce the total number of computations for block matching and also keep the quality of the decompressed image. The computational complexity and the compression performance of the proposed algorithm are compared with those of other block-matching algorithms.
IEEE Transactions on Circuits and Systems for Video Technology, 2002
In many image-coding applications such as web browsing, image databases, and telemedicine, it is ... more In many image-coding applications such as web browsing, image databases, and telemedicine, it is useful to reconstruct only a region of interest (ROI) before the rest of the image is reconstructed. In this paper, an ROI coding functionality is incorporated with the set partitioning in hierarchical trees (SPIHT) algorithm for wavelet-based image coding. By placing a higher emphasis on the transform coefficients pertaining to the ROI, the ROI is coded with higher fidelity than the rest of the image in earlier stages of progressive coding. The general thrust of this research is to identify necessary coefficients in wavelet-transform domain for the decoder to reconstruct the desired region. This new method provides better performance than the previously presented methods. Index Terms-Parent of ROI (PROI), progressive transmission, region of interest (ROI) coding, set partitioning in hierarchical trees (SPIHT), wavelet transform.
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Papers by Hyunwook Park