The Experts below are selected from a list of 13269 Experts worldwide ranked by ideXlab platform

Hurng Sheng Wu - One of the best experts on this subject based on the ideXlab platform.

  • Automatic Distortion Correction of endoscopic images captured with wide-angle zoom lens
    IEEE Transactions on Biomedical Engineering, 2013
    Co-Authors: Tung-ying Lee, Tzu Shan Chang, Chen Hao Wei, Shang-hong Lai, Kai-che Liu, Hurng Sheng Wu
    Abstract:

    Operation in minimally invasive surgery is more difficult since the surgeons perform operations without haptic feedback or depth perception. Moreover, the field of view perceived by the surgeons through endoscopy is usually quite limited. The goal of this paper is to allow surgeons to see wide-angle images from endoscopy without the drawback of lens Distortion. The proposed Distortion Correction process consists of lens calibration and real-time image warping. The calibration step is to estimate the parameters in the lens Distortion model. We propose a fully automatic Hough-entropy-based calibration algorithm, which provides calibration results comparable to the previous manual calibration method. To achieve real-time Correction, we use graphics processing unit to warp the image in parallel. In addition, surgeons may adjust the focal length of a lens during the operation. Real-time Distortion Correction of a zoomable lens is impossible by using traditional calibration methods because the tedious calibration process has to repeat again if focal length is changed. We derive a formula to describe the relationship between the Distortion parameter, focal length, and image boundary. Hence, we can estimate the focal length for a zoomable lens from endoscopic images online and achieve real-time lens Distortion Correction.

Dongil Han - One of the best experts on this subject based on the ideXlab platform.

  • ICIAR - Real-Time digital image warping for display Distortion Correction
    Lecture Notes in Computer Science, 2005
    Co-Authors: Dongil Han
    Abstract:

    This paper describes a digital image warping method which reduces the geometric and optical Distortions in several display devices such as wide screen CRTs, Projection TVs and Projectors. The 2-pass scan line warping algorithm is introduced and it effectively reduces the typical type of display Distortions such as keystone, pincushion, or barrel types. The proposed warping algorithm also considers the image scaling function and renders arbitrary image scaling up or down with display Distortion Correction. The proposed architecture is successfully implemented in hardware and operates at the clock speed around 40 ~ 160MHz. Finally, it is successfully adopted in display Distortion Correction purposes.

Xu Fan - One of the best experts on this subject based on the ideXlab platform.

  • Distortion Correction technique for airborne large-field-of-view lens
    Journal of Computer Applications, 2013
    Co-Authors: Xu Fan
    Abstract:

    For the purpose of correcting the Distortion of the large-field-of-view lens used on aerial cameras, this paper proposed a method using the Matlab calib_ toolbox. By calibrating the captured images of a range of angles-of-view and distances, the internal parameters and Distortion coefficients of the camera were obtained, and the correct mathematical model of Distortion Correction was built. The proposed method made an improvement on the Bouguet method, and extended its applications to Distortion Correction of color images for airborne cameras via subsequent programming. Furthermore, a new and efficient backstepping reconstruction pattern matching method for image-Distortion-rate analysis was proposed, which quantified the level of Distortion. The simulation results show that the proposed method reduces the Distortion rate of color images averagely by about 10%. As all the experimental results indicate, the proposed method is simple and efficient, and it is convenient to be readily transplanted to hardware platform for real-time image Distortion Correction.

Fumio Yamashita - One of the best experts on this subject based on the ideXlab platform.

  • improved volumetric measurement of brain structure with a Distortion Correction procedure using an adni phantom
    Medical Physics, 2013
    Co-Authors: Norihide Maikusa, Hiroyuki Kabasawa, Fumio Yamashita, K Tanaka, Osamu Abe, Atsushi Kawaguchi, Shoma Chiba, Akihiro Kasahara, Nobuhisa Kobayashi, Tetsuya Yuasa
    Abstract:

    Purpose: Serial magnetic resonance imaging (MRI) images acquired from multisite and multivendor MRI scanners are widely used in measuring longitudinal structural changes in the brain. Precise and accurate measurements are important in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease. However, geometric Distortions in MRI images decrease the accuracy and precision of volumetric or morphometric measurements. To solve this problem, the authors suggest a commercially available phantom-based Distortion Correction method that accommodates the variation in geometric Distortion within MRI images obtained with multivendor MRI scanners. Methods: The authors' method is based on image warping using a polynomial function. The method detects fiducial points within a phantom image using phantom analysis software developed by the Mayo Clinic and calculates warping functions for Distortion Correction. To quantify the effectiveness of the authors' method, the authors corrected phantom images obtained from multivendor MRI scanners and calculated the root-mean-square (RMS) of fiducial errors and the circularity ratio as evaluation values. The authors also compared the performance of the authors' method with that of a Distortion Correction method based on a spherical harmonics description of the generic gradient design parameters. Moreover, the authors evaluated whether this Correction improves the test–retest reproducibility of voxel-based morphometry in human studies. Results: A Wilcoxon signed-rank test with uncorrected and corrected images was performed. The root-mean-square errors and circularity ratios for all slices significantly improved (p < 0.0001) after the authors' Distortion Correction. Additionally, the authors' method was significantly better than a Distortion Correction method based on a description of spherical harmonics in improving the Distortion of root-mean-square errors (p < 0.001 and 0.0337, respectively). Moreover, the authors' method reduced the RMS error arising from gradient nonlinearity more than gradwarp methods. In human studies, the coefficient of variation of voxel-based morphometry analysis of the whole brain improved significantly from 3.46% to 2.70% after Distortion Correction of the whole gray matter using the authors' method (Wilcoxon signed-rank test, p < 0.05). Conclusions: The authors proposed a phantom-based Distortion Correction method to improve reproducibility in longitudinal structural brain analysis using multivendor MRI. The authors evaluated the authors' method for phantom images in terms of two geometrical values and for human images in terms of test–retest reproducibility. The results showed that Distortion was corrected significantly using the authors' method. In human studies, the reproducibility of voxel-based morphometry analysis for the whole gray matter significantly improved after Distortion Correction using the authors' method.

  • Effects of Image Distortion Correction on Voxel-based Morphometry
    Magnetic Resonance in Medical Sciences, 2012
    Co-Authors: Masami Goto, Tomomi Kurosu, Hiroyuki Kabasawa, Fumio Yamashita, Hidemasa Takao, Takeshi Iwatsubo, Naoto Hayashi, Tosiaki Miyati, Hiroshi Matsuda
    Abstract:

    PURPOSE: We aimed to show that correcting image Distortion significantly affects brain volumetry using voxel-based morphometry (VBM) and to assess whether the processing of Distortion Correction reduces system dependency. MATERIALS AND METHODS: We obtained contiguous sagittal T(1)-weighted images of the brain from 22 healthy participants using 1.5- and 3-tesla magnetic resonance (MR) scanners, preprocessed images using Statistical Parametric Mapping 5, and tested the relation between Distortion Correction and brain volume using VBM. RESULTS: Local brain volume significantly increased or decreased on corrected images compared with uncorrected images. In addition, the method used to correct image Distortion for gradient nonlinearity produced fewer volumetric errors from MR system variation. CONCLUSION: This is the first VBM study to show more precise volumetry using VBM with corrected images. These results indicate that multi-scanner or multi-site imaging trials require Correction for Distortion induced by gradient nonlinearity.

  • Effects of Image Distortion Correction on Voxel-based Morphometry
    Magnetic Resonance in Medical Sciences, 2012
    Co-Authors: Masami Goto, Tomomi Kurosu, Hiroyuki Kabasawa, Fumio Yamashita, Hidemasa Takao, Takeshi Iwatsubo, Naoto Hayashi, Tosiaki Miyati, Hiroshi Matsuda
    Abstract:

    PURPOSE: We aimed to show that correcting image Distortion significantly affects brain volumetry using voxel-based morphometry (VBM) and to assess whether the processing of Distortion Correction reduces system dependency. MATERIALS AND METHODS: We obtained contiguous sagittal T(1)-weighted images of the brain from 22 healthy participants using 1.5- and 3-tesla magnetic resonance (MR) scanners, preprocessed images using Statistical Parametric Mapping 5, and tested the relation between Distortion Correction and brain volume using VBM. RESULTS: Local brain volume significantly increased or decreased on corrected images compared with uncorrected images. In addition, the method used to correct image Distortion for gradient nonlinearity produced fewer volumetric errors from MR system variation. CONCLUSION: This is the first VBM study to show more precise volumetry using VBM with corrected images. These results indicate that multi-scanner or multi-site imaging trials require Correction for Distortion induced by gradient nonlinearity.

Hiroyuki Kabasawa - One of the best experts on this subject based on the ideXlab platform.

  • improved volumetric measurement of brain structure with a Distortion Correction procedure using an adni phantom
    Medical Physics, 2013
    Co-Authors: Norihide Maikusa, Hiroyuki Kabasawa, Fumio Yamashita, K Tanaka, Osamu Abe, Atsushi Kawaguchi, Shoma Chiba, Akihiro Kasahara, Nobuhisa Kobayashi, Tetsuya Yuasa
    Abstract:

    Purpose: Serial magnetic resonance imaging (MRI) images acquired from multisite and multivendor MRI scanners are widely used in measuring longitudinal structural changes in the brain. Precise and accurate measurements are important in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease. However, geometric Distortions in MRI images decrease the accuracy and precision of volumetric or morphometric measurements. To solve this problem, the authors suggest a commercially available phantom-based Distortion Correction method that accommodates the variation in geometric Distortion within MRI images obtained with multivendor MRI scanners. Methods: The authors' method is based on image warping using a polynomial function. The method detects fiducial points within a phantom image using phantom analysis software developed by the Mayo Clinic and calculates warping functions for Distortion Correction. To quantify the effectiveness of the authors' method, the authors corrected phantom images obtained from multivendor MRI scanners and calculated the root-mean-square (RMS) of fiducial errors and the circularity ratio as evaluation values. The authors also compared the performance of the authors' method with that of a Distortion Correction method based on a spherical harmonics description of the generic gradient design parameters. Moreover, the authors evaluated whether this Correction improves the test–retest reproducibility of voxel-based morphometry in human studies. Results: A Wilcoxon signed-rank test with uncorrected and corrected images was performed. The root-mean-square errors and circularity ratios for all slices significantly improved (p < 0.0001) after the authors' Distortion Correction. Additionally, the authors' method was significantly better than a Distortion Correction method based on a description of spherical harmonics in improving the Distortion of root-mean-square errors (p < 0.001 and 0.0337, respectively). Moreover, the authors' method reduced the RMS error arising from gradient nonlinearity more than gradwarp methods. In human studies, the coefficient of variation of voxel-based morphometry analysis of the whole brain improved significantly from 3.46% to 2.70% after Distortion Correction of the whole gray matter using the authors' method (Wilcoxon signed-rank test, p < 0.05). Conclusions: The authors proposed a phantom-based Distortion Correction method to improve reproducibility in longitudinal structural brain analysis using multivendor MRI. The authors evaluated the authors' method for phantom images in terms of two geometrical values and for human images in terms of test–retest reproducibility. The results showed that Distortion was corrected significantly using the authors' method. In human studies, the reproducibility of voxel-based morphometry analysis for the whole gray matter significantly improved after Distortion Correction using the authors' method.

  • Effects of Image Distortion Correction on Voxel-based Morphometry
    Magnetic Resonance in Medical Sciences, 2012
    Co-Authors: Masami Goto, Tomomi Kurosu, Hiroyuki Kabasawa, Fumio Yamashita, Hidemasa Takao, Takeshi Iwatsubo, Naoto Hayashi, Tosiaki Miyati, Hiroshi Matsuda
    Abstract:

    PURPOSE: We aimed to show that correcting image Distortion significantly affects brain volumetry using voxel-based morphometry (VBM) and to assess whether the processing of Distortion Correction reduces system dependency. MATERIALS AND METHODS: We obtained contiguous sagittal T(1)-weighted images of the brain from 22 healthy participants using 1.5- and 3-tesla magnetic resonance (MR) scanners, preprocessed images using Statistical Parametric Mapping 5, and tested the relation between Distortion Correction and brain volume using VBM. RESULTS: Local brain volume significantly increased or decreased on corrected images compared with uncorrected images. In addition, the method used to correct image Distortion for gradient nonlinearity produced fewer volumetric errors from MR system variation. CONCLUSION: This is the first VBM study to show more precise volumetry using VBM with corrected images. These results indicate that multi-scanner or multi-site imaging trials require Correction for Distortion induced by gradient nonlinearity.

  • Effects of Image Distortion Correction on Voxel-based Morphometry
    Magnetic Resonance in Medical Sciences, 2012
    Co-Authors: Masami Goto, Tomomi Kurosu, Hiroyuki Kabasawa, Fumio Yamashita, Hidemasa Takao, Takeshi Iwatsubo, Naoto Hayashi, Tosiaki Miyati, Hiroshi Matsuda
    Abstract:

    PURPOSE: We aimed to show that correcting image Distortion significantly affects brain volumetry using voxel-based morphometry (VBM) and to assess whether the processing of Distortion Correction reduces system dependency. MATERIALS AND METHODS: We obtained contiguous sagittal T(1)-weighted images of the brain from 22 healthy participants using 1.5- and 3-tesla magnetic resonance (MR) scanners, preprocessed images using Statistical Parametric Mapping 5, and tested the relation between Distortion Correction and brain volume using VBM. RESULTS: Local brain volume significantly increased or decreased on corrected images compared with uncorrected images. In addition, the method used to correct image Distortion for gradient nonlinearity produced fewer volumetric errors from MR system variation. CONCLUSION: This is the first VBM study to show more precise volumetry using VBM with corrected images. These results indicate that multi-scanner or multi-site imaging trials require Correction for Distortion induced by gradient nonlinearity.