The Experts below are selected from a list of 12960 Experts worldwide ranked by ideXlab platform

Gary M Hunninghake - One of the best experts on this subject based on the ideXlab platform.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Background Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems. Forty six patients with biopsy proven IPF were identified from a registry of patients with interstitial lung disease at Brigham and Women’s Hospital in Boston, MA. CT scans for each subject were visually scored using a previously published method. After a semi-automated method was used to segment the lungs from the surrounding tissue, densitometric measurements including the percent high attenuating area, mean lung density, skewness and kurtosis were made for the entirety of each patient’s lungs. A separate, automated tool was used to detect and quantify the percent of lung occupied by interstitial lung features. These analyses were used to create clinical and quantitative CT based risk prediction scores, and the performance of these was compared to the performance of clinical and visual analysis based methods. All of the densitometric measures were correlated with forced vital capacity and diffusing capacity, as were the total amount of interstitial change and the percentage of interstitial change that was honeycombing measured using the Local Histogram method. Higher percent high attenuating area, higher mean lung density, lower skewness, lower kurtosis and a higher percentage of honeycombing were associated with worse transplant free survival. The quantitative CT based risk prediction scores performed similarly to the clinical and visual analysis based methods. Both densitometric and feature based quantitative CT measures correlate with pulmonary function test measures and are associated with transplant free survival. These objective measures may be useful for identifying high risk patients and monitoring disease progression. Further work will be needed to validate these measures and the quantitative imaging based risk prediction scores in other cohorts.

Samuel Y Ash - One of the best experts on this subject based on the ideXlab platform.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Background Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems. Forty six patients with biopsy proven IPF were identified from a registry of patients with interstitial lung disease at Brigham and Women’s Hospital in Boston, MA. CT scans for each subject were visually scored using a previously published method. After a semi-automated method was used to segment the lungs from the surrounding tissue, densitometric measurements including the percent high attenuating area, mean lung density, skewness and kurtosis were made for the entirety of each patient’s lungs. A separate, automated tool was used to detect and quantify the percent of lung occupied by interstitial lung features. These analyses were used to create clinical and quantitative CT based risk prediction scores, and the performance of these was compared to the performance of clinical and visual analysis based methods. All of the densitometric measures were correlated with forced vital capacity and diffusing capacity, as were the total amount of interstitial change and the percentage of interstitial change that was honeycombing measured using the Local Histogram method. Higher percent high attenuating area, higher mean lung density, lower skewness, lower kurtosis and a higher percentage of honeycombing were associated with worse transplant free survival. The quantitative CT based risk prediction scores performed similarly to the clinical and visual analysis based methods. Both densitometric and feature based quantitative CT measures correlate with pulmonary function test measures and are associated with transplant free survival. These objective measures may be useful for identifying high risk patients and monitoring disease progression. Further work will be needed to validate these measures and the quantitative imaging based risk prediction scores in other cohorts.

Seungho Hwang - One of the best experts on this subject based on the ideXlab platform.

  • an advanced contrast enhancement using partially overlapped sub block Histogram equalization
    IEEE Transactions on Circuits and Systems for Video Technology, 2001
    Co-Authors: Seungho Hwang
    Abstract:

    An advanced Histogram-equalization algorithm for contrast enhancement is presented. Histogram equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. It can be classified into two branches according to the transformation function used: global or Local. Global Histogram equalization is simple and fast, but its contrast-enhancement power is relatively low. Local Histogram equalization, on the other hand, can enhance overall contrast more effectively, but the complexity of computation required is very high due to its fully overlapped sub-blocks. In this paper, a low-pass filter-type mask is used to get a nonoverlapped sub-block Histogram-equalization function to produce the high contrast associated with Local Histogram equalization but with the simplicity of global Histogram equalization. This mask also eliminates the blocking effect of nonoverlapped sub-block Histogram-equalization. The low-pass filter-type mask is realized by partially overlapped sub-block Histogram-equalization (POSHE). With the proposed method, since the sub-blocks are much less overlapped, the computation overhead is reduced by a factor of about 100 compared to that of Local Histogram equalization while still achieving high contrast. The proposed algorithm can be used for commercial purposes where high efficiency is required, such as camcorders, closed-circuit cameras, etc.

  • an advanced contrast enhancement using partially overlapped sub block Histogram equalization
    International Symposium on Circuits and Systems, 2000
    Co-Authors: Seungho Hwang
    Abstract:

    In this paper, an advanced Histogram equalization algorithm for contrast enhancement is presented. Histogram equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. Global Histogram equalization is simple and fast, but its contrast enhancement power is relatively low. Local Histogram equalization, on the other hand, can enhance overall contrast more effectively, but the computational complexity is very high due to its fully overlapped sub-blocks. For high contrast and simple calculation, a low pass filter type mask is proposed. The low pass filter type mask is realized by partially overlapped sub-block Histogram equalization (POSHE). With the proposed method, the computation overhead is reduced by a factor of about one hundred compared to that of Local Histogram equalization while still achieving high contrast.

  • an advanced contrast enhancement using partially overlapped sub block Histogram equalization
    International Symposium on Circuits and Systems, 2000
    Co-Authors: Joung-youn Kim, Lee-sup Kim, Seungho Hwang
    Abstract:

    In this paper, an advanced Histogram equalization algorithm for contrast enhancement is presented. Histogram equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. Global Histogram equalization is simple and fast, but its contrast enhancement power is relatively low. Local Histogram equalization, on the other hand, can enhance overall contrast more effectively, but the computational complexity is very high due to its fully overlapped sub-blocks. For high contrast and simple calculation, a low pass filter type mask is proposed. The low pass filter type mask is realized by partially overlapped sub-block Histogram equalization (POSHE). With the proposed method, the computation overhead is reduced by a factor of about one hundred compared to that of Local Histogram equalization while still achieving high contrast.

Jorge Onieva Onieva - One of the best experts on this subject based on the ideXlab platform.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Background Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems. Forty six patients with biopsy proven IPF were identified from a registry of patients with interstitial lung disease at Brigham and Women’s Hospital in Boston, MA. CT scans for each subject were visually scored using a previously published method. After a semi-automated method was used to segment the lungs from the surrounding tissue, densitometric measurements including the percent high attenuating area, mean lung density, skewness and kurtosis were made for the entirety of each patient’s lungs. A separate, automated tool was used to detect and quantify the percent of lung occupied by interstitial lung features. These analyses were used to create clinical and quantitative CT based risk prediction scores, and the performance of these was compared to the performance of clinical and visual analysis based methods. All of the densitometric measures were correlated with forced vital capacity and diffusing capacity, as were the total amount of interstitial change and the percentage of interstitial change that was honeycombing measured using the Local Histogram method. Higher percent high attenuating area, higher mean lung density, lower skewness, lower kurtosis and a higher percentage of honeycombing were associated with worse transplant free survival. The quantitative CT based risk prediction scores performed similarly to the clinical and visual analysis based methods. Both densitometric and feature based quantitative CT measures correlate with pulmonary function test measures and are associated with transplant free survival. These objective measures may be useful for identifying high risk patients and monitoring disease progression. Further work will be needed to validate these measures and the quantitative imaging based risk prediction scores in other cohorts.

Diego Lassala Lopez Vallejo - One of the best experts on this subject based on the ideXlab platform.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Background Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems.

  • densitometric and Local Histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis
    Respiratory Research, 2017
    Co-Authors: Samuel Y Ash, Rola Harmouche, Diego Lassala Lopez Vallejo, Julian A Villalba, Kristoffer Ostridge, River Gunville, Carolyn E Come, Jorge Onieva Onieva, James C Ross, Gary M Hunninghake
    Abstract:

    Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and Local Histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems. Forty six patients with biopsy proven IPF were identified from a registry of patients with interstitial lung disease at Brigham and Women’s Hospital in Boston, MA. CT scans for each subject were visually scored using a previously published method. After a semi-automated method was used to segment the lungs from the surrounding tissue, densitometric measurements including the percent high attenuating area, mean lung density, skewness and kurtosis were made for the entirety of each patient’s lungs. A separate, automated tool was used to detect and quantify the percent of lung occupied by interstitial lung features. These analyses were used to create clinical and quantitative CT based risk prediction scores, and the performance of these was compared to the performance of clinical and visual analysis based methods. All of the densitometric measures were correlated with forced vital capacity and diffusing capacity, as were the total amount of interstitial change and the percentage of interstitial change that was honeycombing measured using the Local Histogram method. Higher percent high attenuating area, higher mean lung density, lower skewness, lower kurtosis and a higher percentage of honeycombing were associated with worse transplant free survival. The quantitative CT based risk prediction scores performed similarly to the clinical and visual analysis based methods. Both densitometric and feature based quantitative CT measures correlate with pulmonary function test measures and are associated with transplant free survival. These objective measures may be useful for identifying high risk patients and monitoring disease progression. Further work will be needed to validate these measures and the quantitative imaging based risk prediction scores in other cohorts.