Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck: Baseline Results

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Standard

Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck : Baseline Results. / Podobnik, Gasper; Ibragimov, Bulat; Strojan, Primoz; Peterlin, Primoz; Vrtovec, Tomaz.

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022. s. 1-4.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Harvard

Podobnik, G, Ibragimov, B, Strojan, P, Peterlin, P & Vrtovec, T 2022, Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck: Baseline Results. i 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, s. 1-4, 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022, Kolkata, Indien, 28/03/2022. https://doi.org/10.1109/ISBI52829.2022.9761433

APA

Podobnik, G., Ibragimov, B., Strojan, P., Peterlin, P., & Vrtovec, T. (2022). Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck: Baseline Results. I 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (s. 1-4). IEEE. https://doi.org/10.1109/ISBI52829.2022.9761433

Vancouver

Podobnik G, Ibragimov B, Strojan P, Peterlin P, Vrtovec T. Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck: Baseline Results. I 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE. 2022. s. 1-4 https://doi.org/10.1109/ISBI52829.2022.9761433

Author

Podobnik, Gasper ; Ibragimov, Bulat ; Strojan, Primoz ; Peterlin, Primoz ; Vrtovec, Tomaz. / Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck : Baseline Results. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022. s. 1-4

Bibtex

@inproceedings{7253e1eda6b64af88412c3cb692b5007,
title = "Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck: Baseline Results",
abstract = "For the head and neck (HaN) cancer, radiotherapy is a mainstay treatment modality that aims to deliver a high radiation dose to the targeted cancerous cells while sparing the nearby healthy organs-at-risk (OARs). A precise three-dimensional segmentation of OARs from computed tomography (CT) images is required for optimal radiation dose distribution calculation, however, so far there has been no evaluation about the impact of the combined analysis of multiple imaging modalities, such as CT and magnetic resonance (MR). For this purpose, we have devised a database of 56 CT and MR images of the same patients with 31 manually delineated OARs, and in this paper we present the baseline segmentation results that were obtained by applying the nnU-Net framework. The resulting average Dice coefficient of 68% and average 95-percentile Hausdorff distance of 8.2mm on a subset of 14 images indicate that nnU-Net serves as a solid baseline method.",
keywords = "automated segmentation, computed tomography, head and neck radiotherapy planning, magnetic resonance, organs-at-risk",
author = "Gasper Podobnik and Bulat Ibragimov and Primoz Strojan and Primoz Peterlin and Tomaz Vrtovec",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022 ; Conference date: 28-03-2022 Through 31-03-2022",
year = "2022",
doi = "10.1109/ISBI52829.2022.9761433",
language = "English",
pages = "1--4",
booktitle = "2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Segmentation of Organs-At-Risk from Ct and Mr Images of the Head and Neck

T2 - 19th IEEE International Symposium on Biomedical Imaging, ISBI 2022

AU - Podobnik, Gasper

AU - Ibragimov, Bulat

AU - Strojan, Primoz

AU - Peterlin, Primoz

AU - Vrtovec, Tomaz

N1 - Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - For the head and neck (HaN) cancer, radiotherapy is a mainstay treatment modality that aims to deliver a high radiation dose to the targeted cancerous cells while sparing the nearby healthy organs-at-risk (OARs). A precise three-dimensional segmentation of OARs from computed tomography (CT) images is required for optimal radiation dose distribution calculation, however, so far there has been no evaluation about the impact of the combined analysis of multiple imaging modalities, such as CT and magnetic resonance (MR). For this purpose, we have devised a database of 56 CT and MR images of the same patients with 31 manually delineated OARs, and in this paper we present the baseline segmentation results that were obtained by applying the nnU-Net framework. The resulting average Dice coefficient of 68% and average 95-percentile Hausdorff distance of 8.2mm on a subset of 14 images indicate that nnU-Net serves as a solid baseline method.

AB - For the head and neck (HaN) cancer, radiotherapy is a mainstay treatment modality that aims to deliver a high radiation dose to the targeted cancerous cells while sparing the nearby healthy organs-at-risk (OARs). A precise three-dimensional segmentation of OARs from computed tomography (CT) images is required for optimal radiation dose distribution calculation, however, so far there has been no evaluation about the impact of the combined analysis of multiple imaging modalities, such as CT and magnetic resonance (MR). For this purpose, we have devised a database of 56 CT and MR images of the same patients with 31 manually delineated OARs, and in this paper we present the baseline segmentation results that were obtained by applying the nnU-Net framework. The resulting average Dice coefficient of 68% and average 95-percentile Hausdorff distance of 8.2mm on a subset of 14 images indicate that nnU-Net serves as a solid baseline method.

KW - automated segmentation

KW - computed tomography

KW - head and neck radiotherapy planning

KW - magnetic resonance

KW - organs-at-risk

UR - http://www.scopus.com/inward/record.url?scp=85129667946&partnerID=8YFLogxK

U2 - 10.1109/ISBI52829.2022.9761433

DO - 10.1109/ISBI52829.2022.9761433

M3 - Article in proceedings

AN - SCOPUS:85129667946

SP - 1

EP - 4

BT - 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)

PB - IEEE

Y2 - 28 March 2022 through 31 March 2022

ER -

ID: 307747906