Standard
Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. / Reimann, Marcel; Won, Jungeun; Takahashi, Hiroyuki; Yaghy, Antonio; Hwang, Yunchan; Ploner, Stefan; Lin, Junhong; Girgis, Jessica; Lam, Kenneth; Chen, Siyu; Waheed, Nadia K.; Maier, Andreas; Fujimoto, James G.
Bildverarbeitung für die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig. red. / Thomas M. Deserno; Heinz Handels; Andreas Maier; Klaus Maier-Hein; Christoph Palm; Thomas Tolxdorff. Springer Science and Business Media Deutschland GmbH, 2023. s. 232-237 (Informatik aktuell).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Reimann, M, Won, J, Takahashi, H, Yaghy, A, Hwang, Y, Ploner, S, Lin, J, Girgis, J, Lam, K, Chen, S, Waheed, NK, Maier, A & Fujimoto, JG 2023,
Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. i TM Deserno, H Handels, A Maier, K Maier-Hein, C Palm & T Tolxdorff (red),
Bildverarbeitung für die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig. Springer Science and Business Media Deutschland GmbH, Informatik aktuell, s. 232-237, Bildverarbeitung für die Medizin Workshop, BVM 2023, Braunschweig, Tyskland,
02/07/2023.
https://doi.org/10.1007/978-3-658-41657-7_50
APA
Reimann, M., Won, J., Takahashi, H., Yaghy, A., Hwang, Y., Ploner, S., Lin, J., Girgis, J., Lam, K., Chen, S., Waheed, N. K., Maier, A., & Fujimoto, J. G. (2023).
Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. I T. M. Deserno, H. Handels, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (red.),
Bildverarbeitung für die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig (s. 232-237). Springer Science and Business Media Deutschland GmbH. Informatik aktuell
https://doi.org/10.1007/978-3-658-41657-7_50
Vancouver
Reimann M, Won J, Takahashi H, Yaghy A, Hwang Y, Ploner S o.a.
Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. I Deserno TM, Handels H, Maier A, Maier-Hein K, Palm C, Tolxdorff T, red., Bildverarbeitung für die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig. Springer Science and Business Media Deutschland GmbH. 2023. s. 232-237. (Informatik aktuell).
https://doi.org/10.1007/978-3-658-41657-7_50
Author
Reimann, Marcel ; Won, Jungeun ; Takahashi, Hiroyuki ; Yaghy, Antonio ; Hwang, Yunchan ; Ploner, Stefan ; Lin, Junhong ; Girgis, Jessica ; Lam, Kenneth ; Chen, Siyu ; Waheed, Nadia K. ; Maier, Andreas ; Fujimoto, James G. / Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography. Bildverarbeitung für die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig. red. / Thomas M. Deserno ; Heinz Handels ; Andreas Maier ; Klaus Maier-Hein ; Christoph Palm ; Thomas Tolxdorff. Springer Science and Business Media Deutschland GmbH, 2023. s. 232-237 (Informatik aktuell).
Bibtex
@inproceedings{7d1a32b97039416b9af59fa104c696c1,
title = "Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography",
abstract = "Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases. Newly visible features are, for example, small hyperreflective specks in age-related macular degeneration. Identifying these new markers is crucial to investigate potential association with disease progression and treatment outcomes. Therefore, it is necessary to reliably detect these features in 3D volumetric scans. Because manual labeling of entire volumes is infeasible a need for automatic detection arises. Labeled datasets are often not publicly available and there are usually large variations in scan protocols and scanner types. Thus, this work focuses on an unsupervised approach that is based on local peak-detection and random walker segmentation to detect small features on each B-scan of the volume.",
author = "Marcel Reimann and Jungeun Won and Hiroyuki Takahashi and Antonio Yaghy and Yunchan Hwang and Stefan Ploner and Junhong Lin and Jessica Girgis and Kenneth Lam and Siyu Chen and Waheed, {Nadia K.} and Andreas Maier and Fujimoto, {James G.}",
note = "Funding Information: Acknowledgement. We acknowledge funding by the National Institutes of Health, project 5-R01-EY011289-36, and the German Research Foundation, project 508075009. Publisher Copyright: {\textcopyright} 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.; Bildverarbeitung f{\"u}r die Medizin Workshop, BVM 2023 ; Conference date: 02-07-2023 Through 04-07-2023",
year = "2023",
doi = "10.1007/978-3-658-41657-7_50",
language = "English",
isbn = "9783658416560",
series = "Informatik aktuell",
pages = "232--237",
editor = "Deserno, {Thomas M.} and Heinz Handels and Andreas Maier and Klaus Maier-Hein and Christoph Palm and Thomas Tolxdorff",
booktitle = "Bildverarbeitung f{\"u}r die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig",
publisher = "Springer Science and Business Media Deutschland GmbH",
address = "Germany",
}
RIS
TY - GEN
T1 - Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography
AU - Reimann, Marcel
AU - Won, Jungeun
AU - Takahashi, Hiroyuki
AU - Yaghy, Antonio
AU - Hwang, Yunchan
AU - Ploner, Stefan
AU - Lin, Junhong
AU - Girgis, Jessica
AU - Lam, Kenneth
AU - Chen, Siyu
AU - Waheed, Nadia K.
AU - Maier, Andreas
AU - Fujimoto, James G.
N1 - Funding Information:
Acknowledgement. We acknowledge funding by the National Institutes of Health, project 5-R01-EY011289-36, and the German Research Foundation, project 508075009.
Publisher Copyright:
© 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.
PY - 2023
Y1 - 2023
N2 - Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases. Newly visible features are, for example, small hyperreflective specks in age-related macular degeneration. Identifying these new markers is crucial to investigate potential association with disease progression and treatment outcomes. Therefore, it is necessary to reliably detect these features in 3D volumetric scans. Because manual labeling of entire volumes is infeasible a need for automatic detection arises. Labeled datasets are often not publicly available and there are usually large variations in scan protocols and scanner types. Thus, this work focuses on an unsupervised approach that is based on local peak-detection and random walker segmentation to detect small features on each B-scan of the volume.
AB - Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases. Newly visible features are, for example, small hyperreflective specks in age-related macular degeneration. Identifying these new markers is crucial to investigate potential association with disease progression and treatment outcomes. Therefore, it is necessary to reliably detect these features in 3D volumetric scans. Because manual labeling of entire volumes is infeasible a need for automatic detection arises. Labeled datasets are often not publicly available and there are usually large variations in scan protocols and scanner types. Thus, this work focuses on an unsupervised approach that is based on local peak-detection and random walker segmentation to detect small features on each B-scan of the volume.
UR - http://www.scopus.com/inward/record.url?scp=85164948017&partnerID=8YFLogxK
U2 - 10.1007/978-3-658-41657-7_50
DO - 10.1007/978-3-658-41657-7_50
M3 - Article in proceedings
AN - SCOPUS:85164948017
SN - 9783658416560
T3 - Informatik aktuell
SP - 232
EP - 237
BT - Bildverarbeitung für die Medizin 2023 Proceedings, German Workshop on Medical Image Computing, Braunschweig
A2 - Deserno, Thomas M.
A2 - Handels, Heinz
A2 - Maier, Andreas
A2 - Maier-Hein, Klaus
A2 - Palm, Christoph
A2 - Tolxdorff, Thomas
PB - Springer Science and Business Media Deutschland GmbH
T2 - Bildverarbeitung für die Medizin Workshop, BVM 2023
Y2 - 2 July 2023 through 4 July 2023
ER -
