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Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. / Dubost, Florian; Dünnwald, Max; Huff, Denver; Scheurmann, Vincent; Schreiber, Frank; Vernooij, Meike W.; Niessen, Wiro; Skalej, Martin; Schreiber, Stefanie; More Authors.

Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019. ed. / Luping Zhou; Duygu Sarikaya; Seyed Mostafa Kia; Stefanie Speidel; Anand Malpani; Daniel Hashimoto; Mohamad Habes; Tommy Löfstedt; Kerstin Ritter; Hongzhi Wang. Springer, 2019. p. 103-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11796 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Dubost, F, Dünnwald, M, Huff, D, Scheurmann, V, Schreiber, F, Vernooij, MW, Niessen, W, Skalej, M, Schreiber, S & More Authors 2019, Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. in L Zhou, D Sarikaya, SM Kia, S Speidel, A Malpani, D Hashimoto, M Habes, T Löfstedt, K Ritter & H Wang (eds), Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11796 LNCS, Springer, pp. 103-111, 2nd International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, Shenzhen, China, 17/10/19. https://doi.org/10.1007/978-3-030-32695-1_12

APA

Dubost, F., Dünnwald, M., Huff, D., Scheurmann, V., Schreiber, F., Vernooij, M. W., ... More Authors (2019). Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. In L. Zhou, D. Sarikaya, S. M. Kia, S. Speidel, A. Malpani, D. Hashimoto, M. Habes, T. Löfstedt, K. Ritter, ... H. Wang (Eds.), Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019 (pp. 103-111). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11796 LNCS). Springer. https://doi.org/10.1007/978-3-030-32695-1_12

Vancouver

Dubost F, Dünnwald M, Huff D, Scheurmann V, Schreiber F, Vernooij MW et al. Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. In Zhou L, Sarikaya D, Kia SM, Speidel S, Malpani A, Hashimoto D, Habes M, Löfstedt T, Ritter K, Wang H, editors, Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019. Springer. 2019. p. 103-111. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-32695-1_12

Author

Dubost, Florian ; Dünnwald, Max ; Huff, Denver ; Scheurmann, Vincent ; Schreiber, Frank ; Vernooij, Meike W. ; Niessen, Wiro ; Skalej, Martin ; Schreiber, Stefanie ; More Authors. / Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites. Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019. editor / Luping Zhou ; Duygu Sarikaya ; Seyed Mostafa Kia ; Stefanie Speidel ; Anand Malpani ; Daniel Hashimoto ; Mohamad Habes ; Tommy Löfstedt ; Kerstin Ritter ; Hongzhi Wang. Springer, 2019. pp. 103-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{a1b574d7f3464df7ac1c9e6c6f900f2c,
title = "Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites",
abstract = "Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, and are a marker of cerebral small vessel disease. Most studies use time-consuming and subjective visual scoring to assess these structures. Recently, automated methods to quantify enlarged perivascular spaces have been proposed. Most of these methods have been evaluated only in high resolution scans acquired in controlled research settings. We evaluate and compare two recently published automated methods for the quantification of enlarged perivascular spaces in 76 clinical scans acquired from 9 different scanners. Both methods are neural networks trained on high resolution research scans and are applied without fine-tuning the networks’ parameters. By adapting the preprocessing of clinical scans, regions of interest similar to those computed from research scans can be processed. The first method estimates …",
keywords = "Clinical MRI, Deep learning, Perivascular spaces",
author = "Florian Dubost and Max D{\"u}nnwald and Denver Huff and Vincent Scheurmann and Frank Schreiber and Vernooij, {Meike W.} and Wiro Niessen and Martin Skalej and Stefanie Schreiber and {More Authors}",
year = "2019",
doi = "10.1007/978-3-030-32695-1_12",
language = "English",
isbn = "9783030326944",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "103--111",
editor = "Luping Zhou and Duygu Sarikaya and Kia, {Seyed Mostafa} and Stefanie Speidel and Anand Malpani and Daniel Hashimoto and Mohamad Habes and Tommy L{\"o}fstedt and Kerstin Ritter and Hongzhi Wang",
booktitle = "Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019",

}

RIS

TY - GEN

T1 - Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites

AU - Dubost, Florian

AU - Dünnwald, Max

AU - Huff, Denver

AU - Scheurmann, Vincent

AU - Schreiber, Frank

AU - Vernooij, Meike W.

AU - Niessen, Wiro

AU - Skalej, Martin

AU - Schreiber, Stefanie

AU - More Authors, null

PY - 2019

Y1 - 2019

N2 - Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, and are a marker of cerebral small vessel disease. Most studies use time-consuming and subjective visual scoring to assess these structures. Recently, automated methods to quantify enlarged perivascular spaces have been proposed. Most of these methods have been evaluated only in high resolution scans acquired in controlled research settings. We evaluate and compare two recently published automated methods for the quantification of enlarged perivascular spaces in 76 clinical scans acquired from 9 different scanners. Both methods are neural networks trained on high resolution research scans and are applied without fine-tuning the networks’ parameters. By adapting the preprocessing of clinical scans, regions of interest similar to those computed from research scans can be processed. The first method estimates …

AB - Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, and are a marker of cerebral small vessel disease. Most studies use time-consuming and subjective visual scoring to assess these structures. Recently, automated methods to quantify enlarged perivascular spaces have been proposed. Most of these methods have been evaluated only in high resolution scans acquired in controlled research settings. We evaluate and compare two recently published automated methods for the quantification of enlarged perivascular spaces in 76 clinical scans acquired from 9 different scanners. Both methods are neural networks trained on high resolution research scans and are applied without fine-tuning the networks’ parameters. By adapting the preprocessing of clinical scans, regions of interest similar to those computed from research scans can be processed. The first method estimates …

KW - Clinical MRI

KW - Deep learning

KW - Perivascular spaces

UR - http://www.scopus.com/inward/record.url?scp=85075574412&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-32695-1_12

DO - 10.1007/978-3-030-32695-1_12

M3 - Conference contribution

SN - 9783030326944

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 103

EP - 111

BT - Proceedings of 2nd International Workshop on Context-Aware Surgical Theaters,OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging, MLCN 2019

A2 - Zhou, Luping

A2 - Sarikaya, Duygu

A2 - Kia, Seyed Mostafa

A2 - Speidel, Stefanie

A2 - Malpani, Anand

A2 - Hashimoto, Daniel

A2 - Habes, Mohamad

A2 - Löfstedt, Tommy

A2 - Ritter, Kerstin

A2 - Wang, Hongzhi

PB - Springer

ER -

ID: 66772775