Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis

P. Strenge; B. Lange; C. Grill; W. Draxinger; M. M. Bonsanto; C. Hagel; R. Huber; R. Brinkmann

doi:10.1117/12.2545659

Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis

P. Strenge, B. Lange, C. Grill, W. Draxinger, M. M. Bonsanto, C. Hagel, R. Huber, R. Brinkmann

University Hospital Hamburg-Eppendorf

Abstract

The aim of this work is the creation of segmented data set consisting of optical coherence tomography (OCT) scans, which were taken of brain tumor tissue with different tumor infiltration rates. In an ongoing clinical study more than 140 human brain samples with different infiltration grades were recorded ex vivo with two OCT systems, a spectral domain OCT system and a swept-source OCT system that uses a 1310 nm Fourier domain mode locked laser. The histological analysis of the recorded samples builds the ground truth for labeling the corresponding OCT B-Scans. The segmented data set gained from this process will be used to train a classification algorithm, taking into account structural and optical properties such as the attenuation coefficient. In the future the classification algorithm together with a microscope integrated OCT system will be used for the in vivo identification of brain tumors as a guidance tool for the surgeon to increase tumor resection efficiency.

Original language	English
Title of host publication	Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV
Editors	Joseph A. Izatt, James G. Fujimoto
Number of pages	8
Volume	11228
Publisher	SPIE
Publication date	21.02.2020
Article number	112282O
ISBN (Print)	978-151063219-6
DOIs	https://doi.org/10.1117/12.2545659
Publication status	Published - 21.02.2020
Event	Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV 2020 - San Francisco, United States Duration: 03.02.2020 → 05.02.2020 Conference number: 158647

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Academic Focus: Biomedical Engineering

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Strenge, P., Lange, B., Grill, C., Draxinger, W., Bonsanto, M. M., Hagel, C., Huber, R., & Brinkmann, R. (2020). Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis. In J. A. Izatt, & J. G. Fujimoto (Eds.), Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV (Vol. 11228). Article 112282O (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11228). SPIE. https://doi.org/10.1117/12.2545659

@inproceedings{ebd7f6e6906743669ba298f931b9a082,

title = "Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis",

abstract = "The aim of this work is the creation of segmented data set consisting of optical coherence tomography (OCT) scans, which were taken of brain tumor tissue with different tumor infiltration rates. In an ongoing clinical study more than 140 human brain samples with different infiltration grades were recorded ex vivo with two OCT systems, a spectral domain OCT system and a swept-source OCT system that uses a 1310 nm Fourier domain mode locked laser. The histological analysis of the recorded samples builds the ground truth for labeling the corresponding OCT B-Scans. The segmented data set gained from this process will be used to train a classification algorithm, taking into account structural and optical properties such as the attenuation coefficient. In the future the classification algorithm together with a microscope integrated OCT system will be used for the in vivo identification of brain tumors as a guidance tool for the surgeon to increase tumor resection efficiency.",

author = "P. Strenge and B. Lange and C. Grill and W. Draxinger and Bonsanto, {M. M.} and C. Hagel and R. Huber and R. Brinkmann",

note = "Funding Information: This research is funded by the Federal Ministry of Education and Research Grants No.: 13GW0227A, 13GW0227B 13GW0227C and the European Union project ENCOMOLE-2i (Horizon 2020, ERC CoG no. 646669). Evaluation of human brain tissue was approved by Ethics committee of University Medical Center Schleswig-Holstein, Campus L{\"u}beck, Germany, No.: 18-204. Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV 2020 ; Conference date: 03-02-2020 Through 05-02-2020",

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language = "English",

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series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

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Strenge, P , Lange, B, Grill, C, Draxinger, W , Bonsanto, MM, Hagel, C, Huber, R & Brinkmann, R 2020, Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis. in JA Izatt & JG Fujimoto (eds), Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV. vol. 11228, 112282O, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11228, SPIE, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV 2020, San Francisco, California, United States, 03.02.20. https://doi.org/10.1117/12.2545659

Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis. / Strenge, P.; Lange, B.; Grill, C. et al.
Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV. ed. / Joseph A. Izatt; James G. Fujimoto. Vol. 11228 SPIE, 2020. 112282O (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11228).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

TY - GEN

T1 - Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis

AU - Strenge, P.

AU - Lange, B.

AU - Grill, C.

AU - Draxinger, W.

AU - Bonsanto, M. M.

AU - Hagel, C.

AU - Huber, R.

AU - Brinkmann, R.

N1 - Conference code: 158647

PY - 2020/2/21

Y1 - 2020/2/21

N2 - The aim of this work is the creation of segmented data set consisting of optical coherence tomography (OCT) scans, which were taken of brain tumor tissue with different tumor infiltration rates. In an ongoing clinical study more than 140 human brain samples with different infiltration grades were recorded ex vivo with two OCT systems, a spectral domain OCT system and a swept-source OCT system that uses a 1310 nm Fourier domain mode locked laser. The histological analysis of the recorded samples builds the ground truth for labeling the corresponding OCT B-Scans. The segmented data set gained from this process will be used to train a classification algorithm, taking into account structural and optical properties such as the attenuation coefficient. In the future the classification algorithm together with a microscope integrated OCT system will be used for the in vivo identification of brain tumors as a guidance tool for the surgeon to increase tumor resection efficiency.

AB - The aim of this work is the creation of segmented data set consisting of optical coherence tomography (OCT) scans, which were taken of brain tumor tissue with different tumor infiltration rates. In an ongoing clinical study more than 140 human brain samples with different infiltration grades were recorded ex vivo with two OCT systems, a spectral domain OCT system and a swept-source OCT system that uses a 1310 nm Fourier domain mode locked laser. The histological analysis of the recorded samples builds the ground truth for labeling the corresponding OCT B-Scans. The segmented data set gained from this process will be used to train a classification algorithm, taking into account structural and optical properties such as the attenuation coefficient. In the future the classification algorithm together with a microscope integrated OCT system will be used for the in vivo identification of brain tumors as a guidance tool for the surgeon to increase tumor resection efficiency.

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DO - 10.1117/12.2545659

M3 - Conference contribution

SN - 978-151063219-6

VL - 11228

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV

A2 - Izatt, Joseph A.

A2 - Fujimoto, James G.

PB - SPIE

T2 - Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV 2020

Y2 - 3 February 2020 through 5 February 2020

ER -

Strenge P , Lange B, Grill C, Draxinger W , Bonsanto MM, Hagel C et al. Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis. In Izatt JA, Fujimoto JG, editors, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV. Vol. 11228. SPIE. 2020. 112282O. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.2545659

Segmented OCT data set for depth resolved brain tumor detection validated by histological analysis

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