Longitudinal multiple sclerosis lesion segmentation: Resource and challenge
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Carass, Aaron [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Schlagwörter: |
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| Umfang: |
26 |
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| Übergeordnetes Werk: |
Enthalten in: Field study of a soft X-ray aerosol neutralizer combined with electrostatic classifiers for nanoparticle size distribution measurements - Nicosia, Alessia ELSEVIER, 2017, a journal of brain function, Orlando, Fla |
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| Übergeordnetes Werk: |
volume:148 ; year:2017 ; day:1 ; month:03 ; pages:77-102 ; extent:26 |
| Links: |
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| DOI / URN: |
10.1016/j.neuroimage.2016.12.064 |
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| Katalog-ID: |
ELV020472692 |
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| 520 | |a In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. | ||
| 520 | |a In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. | ||
| 650 | 7 | |a Multiple sclerosis |2 Elsevier | |
| 650 | 7 | |a Magnetic resonance imaging |2 Elsevier | |
| 700 | 1 | |a Roy, Snehashis |4 oth | |
| 700 | 1 | |a Jog, Amod |4 oth | |
| 700 | 1 | |a Cuzzocreo, Jennifer L. |4 oth | |
| 700 | 1 | |a Magrath, Elizabeth |4 oth | |
| 700 | 1 | |a Gherman, Adrian |4 oth | |
| 700 | 1 | |a Button, Julia |4 oth | |
| 700 | 1 | |a Nguyen, James |4 oth | |
| 700 | 1 | |a Prados, Ferran |4 oth | |
| 700 | 1 | |a Sudre, Carole H. |4 oth | |
| 700 | 1 | |a Jorge Cardoso, Manuel |4 oth | |
| 700 | 1 | |a Cawley, Niamh |4 oth | |
| 700 | 1 | |a Ciccarelli, Olga |4 oth | |
| 700 | 1 | |a Wheeler-Kingshott, Claudia A.M. |4 oth | |
| 700 | 1 | |a Ourselin, Sébastien |4 oth | |
| 700 | 1 | |a Catanese, Laurence |4 oth | |
| 700 | 1 | |a Deshpande, Hrishikesh |4 oth | |
| 700 | 1 | |a Maurel, Pierre |4 oth | |
| 700 | 1 | |a Commowick, Olivier |4 oth | |
| 700 | 1 | |a Barillot, Christian |4 oth | |
| 700 | 1 | |a Tomas-Fernandez, Xavier |4 oth | |
| 700 | 1 | |a Warfield, Simon K. |4 oth | |
| 700 | 1 | |a Vaidya, Suthirth |4 oth | |
| 700 | 1 | |a Chunduru, Abhijith |4 oth | |
| 700 | 1 | |a Muthuganapathy, Ramanathan |4 oth | |
| 700 | 1 | |a Krishnamurthi, Ganapathy |4 oth | |
| 700 | 1 | |a Jesson, Andrew |4 oth | |
| 700 | 1 | |a Arbel, Tal |4 oth | |
| 700 | 1 | |a Maier, Oskar |4 oth | |
| 700 | 1 | |a Handels, Heinz |4 oth | |
| 700 | 1 | |a Iheme, Leonardo O. |4 oth | |
| 700 | 1 | |a Unay, Devrim |4 oth | |
| 700 | 1 | |a Jain, Saurabh |4 oth | |
| 700 | 1 | |a Sima, Diana M. |4 oth | |
| 700 | 1 | |a Smeets, Dirk |4 oth | |
| 700 | 1 | |a Ghafoorian, Mohsen |4 oth | |
| 700 | 1 | |a Platel, Bram |4 oth | |
| 700 | 1 | |a Birenbaum, Ariel |4 oth | |
| 700 | 1 | |a Greenspan, Hayit |4 oth | |
| 700 | 1 | |a Bazin, Pierre-Louis |4 oth | |
| 700 | 1 | |a Calabresi, Peter A. |4 oth | |
| 700 | 1 | |a Crainiceanu, Ciprian M. |4 oth | |
| 700 | 1 | |a Ellingsen, Lotta M. |4 oth | |
| 700 | 1 | |a Reich, Daniel S. |4 oth | |
| 700 | 1 | |a Prince, Jerry L. |4 oth | |
| 700 | 1 | |a Pham, Dzung L. |4 oth | |
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10.1016/j.neuroimage.2016.12.064 doi GBV00000000000062A.pica (DE-627)ELV020472692 (ELSEVIER)S1053-8119(16)30781-9 DE-627 ger DE-627 rakwb eng 610 610 DE-600 Carass, Aaron verfasserin aut Longitudinal multiple sclerosis lesion segmentation: Resource and challenge 2017transfer abstract 26 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. Multiple sclerosis Elsevier Magnetic resonance imaging Elsevier Roy, Snehashis oth Jog, Amod oth Cuzzocreo, Jennifer L. oth Magrath, Elizabeth oth Gherman, Adrian oth Button, Julia oth Nguyen, James oth Prados, Ferran oth Sudre, Carole H. oth Jorge Cardoso, Manuel oth Cawley, Niamh oth Ciccarelli, Olga oth Wheeler-Kingshott, Claudia A.M. oth Ourselin, Sébastien oth Catanese, Laurence oth Deshpande, Hrishikesh oth Maurel, Pierre oth Commowick, Olivier oth Barillot, Christian oth Tomas-Fernandez, Xavier oth Warfield, Simon K. oth Vaidya, Suthirth oth Chunduru, Abhijith oth Muthuganapathy, Ramanathan oth Krishnamurthi, Ganapathy oth Jesson, Andrew oth Arbel, Tal oth Maier, Oskar oth Handels, Heinz oth Iheme, Leonardo O. oth Unay, Devrim oth Jain, Saurabh oth Sima, Diana M. oth Smeets, Dirk oth Ghafoorian, Mohsen oth Platel, Bram oth Birenbaum, Ariel oth Greenspan, Hayit oth Bazin, Pierre-Louis oth Calabresi, Peter A. oth Crainiceanu, Ciprian M. oth Ellingsen, Lotta M. oth Reich, Daniel S. oth Prince, Jerry L. oth Pham, Dzung L. oth Enthalten in Academic Press Nicosia, Alessia ELSEVIER Field study of a soft X-ray aerosol neutralizer combined with electrostatic classifiers for nanoparticle size distribution measurements 2017 a journal of brain function Orlando, Fla (DE-627)ELV001942808 volume:148 year:2017 day:1 month:03 pages:77-102 extent:26 https://doi.org/10.1016/j.neuroimage.2016.12.064 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 148 2017 1 0301 77-102 26 045F 610 |
| spelling |
10.1016/j.neuroimage.2016.12.064 doi GBV00000000000062A.pica (DE-627)ELV020472692 (ELSEVIER)S1053-8119(16)30781-9 DE-627 ger DE-627 rakwb eng 610 610 DE-600 Carass, Aaron verfasserin aut Longitudinal multiple sclerosis lesion segmentation: Resource and challenge 2017transfer abstract 26 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. Multiple sclerosis Elsevier Magnetic resonance imaging Elsevier Roy, Snehashis oth Jog, Amod oth Cuzzocreo, Jennifer L. oth Magrath, Elizabeth oth Gherman, Adrian oth Button, Julia oth Nguyen, James oth Prados, Ferran oth Sudre, Carole H. oth Jorge Cardoso, Manuel oth Cawley, Niamh oth Ciccarelli, Olga oth Wheeler-Kingshott, Claudia A.M. oth Ourselin, Sébastien oth Catanese, Laurence oth Deshpande, Hrishikesh oth Maurel, Pierre oth Commowick, Olivier oth Barillot, Christian oth Tomas-Fernandez, Xavier oth Warfield, Simon K. oth Vaidya, Suthirth oth Chunduru, Abhijith oth Muthuganapathy, Ramanathan oth Krishnamurthi, Ganapathy oth Jesson, Andrew oth Arbel, Tal oth Maier, Oskar oth Handels, Heinz oth Iheme, Leonardo O. oth Unay, Devrim oth Jain, Saurabh oth Sima, Diana M. oth Smeets, Dirk oth Ghafoorian, Mohsen oth Platel, Bram oth Birenbaum, Ariel oth Greenspan, Hayit oth Bazin, Pierre-Louis oth Calabresi, Peter A. oth Crainiceanu, Ciprian M. oth Ellingsen, Lotta M. oth Reich, Daniel S. oth Prince, Jerry L. oth Pham, Dzung L. oth Enthalten in Academic Press Nicosia, Alessia ELSEVIER Field study of a soft X-ray aerosol neutralizer combined with electrostatic classifiers for nanoparticle size distribution measurements 2017 a journal of brain function Orlando, Fla (DE-627)ELV001942808 volume:148 year:2017 day:1 month:03 pages:77-102 extent:26 https://doi.org/10.1016/j.neuroimage.2016.12.064 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 148 2017 1 0301 77-102 26 045F 610 |
| allfields_unstemmed |
10.1016/j.neuroimage.2016.12.064 doi GBV00000000000062A.pica (DE-627)ELV020472692 (ELSEVIER)S1053-8119(16)30781-9 DE-627 ger DE-627 rakwb eng 610 610 DE-600 Carass, Aaron verfasserin aut Longitudinal multiple sclerosis lesion segmentation: Resource and challenge 2017transfer abstract 26 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. Multiple sclerosis Elsevier Magnetic resonance imaging Elsevier Roy, Snehashis oth Jog, Amod oth Cuzzocreo, Jennifer L. oth Magrath, Elizabeth oth Gherman, Adrian oth Button, Julia oth Nguyen, James oth Prados, Ferran oth Sudre, Carole H. oth Jorge Cardoso, Manuel oth Cawley, Niamh oth Ciccarelli, Olga oth Wheeler-Kingshott, Claudia A.M. oth Ourselin, Sébastien oth Catanese, Laurence oth Deshpande, Hrishikesh oth Maurel, Pierre oth Commowick, Olivier oth Barillot, Christian oth Tomas-Fernandez, Xavier oth Warfield, Simon K. oth Vaidya, Suthirth oth Chunduru, Abhijith oth Muthuganapathy, Ramanathan oth Krishnamurthi, Ganapathy oth Jesson, Andrew oth Arbel, Tal oth Maier, Oskar oth Handels, Heinz oth Iheme, Leonardo O. oth Unay, Devrim oth Jain, Saurabh oth Sima, Diana M. oth Smeets, Dirk oth Ghafoorian, Mohsen oth Platel, Bram oth Birenbaum, Ariel oth Greenspan, Hayit oth Bazin, Pierre-Louis oth Calabresi, Peter A. oth Crainiceanu, Ciprian M. oth Ellingsen, Lotta M. oth Reich, Daniel S. oth Prince, Jerry L. oth Pham, Dzung L. oth Enthalten in Academic Press Nicosia, Alessia ELSEVIER Field study of a soft X-ray aerosol neutralizer combined with electrostatic classifiers for nanoparticle size distribution measurements 2017 a journal of brain function Orlando, Fla (DE-627)ELV001942808 volume:148 year:2017 day:1 month:03 pages:77-102 extent:26 https://doi.org/10.1016/j.neuroimage.2016.12.064 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 148 2017 1 0301 77-102 26 045F 610 |
| allfieldsGer |
10.1016/j.neuroimage.2016.12.064 doi GBV00000000000062A.pica (DE-627)ELV020472692 (ELSEVIER)S1053-8119(16)30781-9 DE-627 ger DE-627 rakwb eng 610 610 DE-600 Carass, Aaron verfasserin aut Longitudinal multiple sclerosis lesion segmentation: Resource and challenge 2017transfer abstract 26 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. Multiple sclerosis Elsevier Magnetic resonance imaging Elsevier Roy, Snehashis oth Jog, Amod oth Cuzzocreo, Jennifer L. oth Magrath, Elizabeth oth Gherman, Adrian oth Button, Julia oth Nguyen, James oth Prados, Ferran oth Sudre, Carole H. oth Jorge Cardoso, Manuel oth Cawley, Niamh oth Ciccarelli, Olga oth Wheeler-Kingshott, Claudia A.M. oth Ourselin, Sébastien oth Catanese, Laurence oth Deshpande, Hrishikesh oth Maurel, Pierre oth Commowick, Olivier oth Barillot, Christian oth Tomas-Fernandez, Xavier oth Warfield, Simon K. oth Vaidya, Suthirth oth Chunduru, Abhijith oth Muthuganapathy, Ramanathan oth Krishnamurthi, Ganapathy oth Jesson, Andrew oth Arbel, Tal oth Maier, Oskar oth Handels, Heinz oth Iheme, Leonardo O. oth Unay, Devrim oth Jain, Saurabh oth Sima, Diana M. oth Smeets, Dirk oth Ghafoorian, Mohsen oth Platel, Bram oth Birenbaum, Ariel oth Greenspan, Hayit oth Bazin, Pierre-Louis oth Calabresi, Peter A. oth Crainiceanu, Ciprian M. oth Ellingsen, Lotta M. oth Reich, Daniel S. oth Prince, Jerry L. oth Pham, Dzung L. oth Enthalten in Academic Press Nicosia, Alessia ELSEVIER Field study of a soft X-ray aerosol neutralizer combined with electrostatic classifiers for nanoparticle size distribution measurements 2017 a journal of brain function Orlando, Fla (DE-627)ELV001942808 volume:148 year:2017 day:1 month:03 pages:77-102 extent:26 https://doi.org/10.1016/j.neuroimage.2016.12.064 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 148 2017 1 0301 77-102 26 045F 610 |
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10.1016/j.neuroimage.2016.12.064 doi GBV00000000000062A.pica (DE-627)ELV020472692 (ELSEVIER)S1053-8119(16)30781-9 DE-627 ger DE-627 rakwb eng 610 610 DE-600 Carass, Aaron verfasserin aut Longitudinal multiple sclerosis lesion segmentation: Resource and challenge 2017transfer abstract 26 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. Multiple sclerosis Elsevier Magnetic resonance imaging Elsevier Roy, Snehashis oth Jog, Amod oth Cuzzocreo, Jennifer L. oth Magrath, Elizabeth oth Gherman, Adrian oth Button, Julia oth Nguyen, James oth Prados, Ferran oth Sudre, Carole H. oth Jorge Cardoso, Manuel oth Cawley, Niamh oth Ciccarelli, Olga oth Wheeler-Kingshott, Claudia A.M. oth Ourselin, Sébastien oth Catanese, Laurence oth Deshpande, Hrishikesh oth Maurel, Pierre oth Commowick, Olivier oth Barillot, Christian oth Tomas-Fernandez, Xavier oth Warfield, Simon K. oth Vaidya, Suthirth oth Chunduru, Abhijith oth Muthuganapathy, Ramanathan oth Krishnamurthi, Ganapathy oth Jesson, Andrew oth Arbel, Tal oth Maier, Oskar oth Handels, Heinz oth Iheme, Leonardo O. oth Unay, Devrim oth Jain, Saurabh oth Sima, Diana M. oth Smeets, Dirk oth Ghafoorian, Mohsen oth Platel, Bram oth Birenbaum, Ariel oth Greenspan, Hayit oth Bazin, Pierre-Louis oth Calabresi, Peter A. oth Crainiceanu, Ciprian M. oth Ellingsen, Lotta M. oth Reich, Daniel S. oth Prince, Jerry L. oth Pham, Dzung L. oth Enthalten in Academic Press Nicosia, Alessia ELSEVIER Field study of a soft X-ray aerosol neutralizer combined with electrostatic classifiers for nanoparticle size distribution measurements 2017 a journal of brain function Orlando, Fla (DE-627)ELV001942808 volume:148 year:2017 day:1 month:03 pages:77-102 extent:26 https://doi.org/10.1016/j.neuroimage.2016.12.064 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 148 2017 1 0301 77-102 26 045F 610 |
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longitudinal multiple sclerosis lesion segmentation: resource and challenge |
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Longitudinal multiple sclerosis lesion segmentation: Resource and challenge |
| abstract |
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. |
| abstractGer |
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. |
| abstract_unstemmed |
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 2 The Challenge Evaluation Website is: http://smart-stats-tools.org/lesion-challenge-2015 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. |
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Longitudinal multiple sclerosis lesion segmentation: Resource and challenge |
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Roy, Snehashis Jog, Amod Cuzzocreo, Jennifer L. Magrath, Elizabeth Gherman, Adrian Button, Julia Nguyen, James Prados, Ferran Sudre, Carole H. Jorge Cardoso, Manuel Cawley, Niamh Ciccarelli, Olga Wheeler-Kingshott, Claudia A.M. Ourselin, Sébastien Catanese, Laurence Deshpande, Hrishikesh Maurel, Pierre Commowick, Olivier Barillot, Christian Tomas-Fernandez, Xavier Warfield, Simon K. Vaidya, Suthirth Chunduru, Abhijith Muthuganapathy, Ramanathan Krishnamurthi, Ganapathy Jesson, Andrew Arbel, Tal Maier, Oskar Handels, Heinz Iheme, Leonardo O. Unay, Devrim Jain, Saurabh Sima, Diana M. Smeets, Dirk Ghafoorian, Mohsen Platel, Bram Birenbaum, Ariel Greenspan, Hayit Bazin, Pierre-Louis Calabresi, Peter A. Crainiceanu, Ciprian M. Ellingsen, Lotta M. Reich, Daniel S. Prince, Jerry L. Pham, Dzung L. |
| author2Str |
Roy, Snehashis Jog, Amod Cuzzocreo, Jennifer L. Magrath, Elizabeth Gherman, Adrian Button, Julia Nguyen, James Prados, Ferran Sudre, Carole H. Jorge Cardoso, Manuel Cawley, Niamh Ciccarelli, Olga Wheeler-Kingshott, Claudia A.M. Ourselin, Sébastien Catanese, Laurence Deshpande, Hrishikesh Maurel, Pierre Commowick, Olivier Barillot, Christian Tomas-Fernandez, Xavier Warfield, Simon K. Vaidya, Suthirth Chunduru, Abhijith Muthuganapathy, Ramanathan Krishnamurthi, Ganapathy Jesson, Andrew Arbel, Tal Maier, Oskar Handels, Heinz Iheme, Leonardo O. Unay, Devrim Jain, Saurabh Sima, Diana M. Smeets, Dirk Ghafoorian, Mohsen Platel, Bram Birenbaum, Ariel Greenspan, Hayit Bazin, Pierre-Louis Calabresi, Peter A. Crainiceanu, Ciprian M. Ellingsen, Lotta M. Reich, Daniel S. Prince, Jerry L. Pham, Dzung L. |
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| doi_str |
10.1016/j.neuroimage.2016.12.064 |
| up_date |
2024-07-06T17:41:56.200Z |
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