The Experts below are selected from a list of 7152 Experts worldwide ranked by ideXlab platform
Ali Fatemi - One of the best experts on this subject based on the ideXlab platform.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical Physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE: Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS: Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS: The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
Morteza Pishghadam - One of the best experts on this subject based on the ideXlab platform.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical Physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE: Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS: Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS: The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
Kamran Kazemi - One of the best experts on this subject based on the ideXlab platform.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical Physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE: Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS: Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS: The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
Mansour Zabihzadeh - One of the best experts on this subject based on the ideXlab platform.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical Physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE: Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS: Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS: The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
Mojtaba Hoseini-ghahfarokhi - One of the best experts on this subject based on the ideXlab platform.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical Physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE: Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS: Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS: The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.
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A new approach to automatic fetal Brain extraction from MRI using a variational level set method.
Medical physics, 2019Co-Authors: Morteza Pishghadam, Kamran Kazemi, Sirous Nekooei, Farrokh Seilanian-toosi, Mojtaba Hoseini-ghahfarokhi, Mansour Zabihzadeh, Ali FatemiAbstract:BACKGROUND AND PURPOSE Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal Brain, it is not possible to use methods routinely used for extraction of adult Brains for fetal Brains. The aim of the present study was to use a variational level set approach to extract fetal Brain from T2-weighted MR images of the womb. METHODS Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the Fetus Brain was automatically determined. Then, the variational level set was used for Fetus Brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal Brain from MR images was confirmed, both statistically and visually through cross-validation.