Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation

Abhishek Srivastava; Debesh Jha; Bulent Aydogan; Mohamed E. Abazeed; Ulas Bagci

doi:10.1007/978-3-031-27420-6_11

Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation

Abhishek Srivastava^*, Debesh Jha, Bulent Aydogan, Mohamed E. Abazeed, Ulas Bagci

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Head and Neck (H &N) organ-at-risk (OAR) and tumor segmentations are an essential component of radiation therapy planning. The varying anatomic locations and dimensions of H &N nodal Gross Tumor Volumes (GTVn) and H &N primary gross tumor volume (GTVp) are difficult to obtain due to lack of accurate and reliable delineation methods. The downstream effect of incorrect segmentation can result in unnecessary irradiation of normal organs. Towards a fully automated radiation therapy planning algorithm, we explore the efficacy of multi-scale fusion based deep learning architectures for accurately segmenting H &N tumors from medical scans. Team Name: M &H_lab_NU.

Original language	English (US)
Title of host publication	Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings
Editors	Vincent Andrearczyk, Valentin Oreiller, Adrien Depeursinge, Mathieu Hatt
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	107-113
Number of pages	7
ISBN (Print)	9783031274190
DOIs	https://doi.org/10.1007/978-3-031-27420-6_11
State	Published - 2023
Event	3rd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, held in Conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022 - Singapore, Singapore Duration: Sep 22 2022 → Sep 22 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13626 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, held in Conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022
Country/Territory	Singapore
City	Singapore
Period	9/22/22 → 9/22/22

Keywords

Head and neck
Multi-scale fusion
Tumor segmentation

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-27420-6_11

Cite this

Srivastava, A., Jha, D., Aydogan, B., Abazeed, M. E., & Bagci, U. (2023). Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation. In V. Andrearczyk, V. Oreiller, A. Depeursinge, & M. Hatt (Eds.), Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings (pp. 107-113). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13626 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-27420-6_11

Srivastava, Abhishek ; Jha, Debesh ; Aydogan, Bulent et al. / Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation. Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings. editor / Vincent Andrearczyk ; Valentin Oreiller ; Adrien Depeursinge ; Mathieu Hatt. Springer Science and Business Media Deutschland GmbH, 2023. pp. 107-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Head and Neck (H &N) organ-at-risk (OAR) and tumor segmentations are an essential component of radiation therapy planning. The varying anatomic locations and dimensions of H &N nodal Gross Tumor Volumes (GTVn) and H &N primary gross tumor volume (GTVp) are difficult to obtain due to lack of accurate and reliable delineation methods. The downstream effect of incorrect segmentation can result in unnecessary irradiation of normal organs. Towards a fully automated radiation therapy planning algorithm, we explore the efficacy of multi-scale fusion based deep learning architectures for accurately segmenting H &N tumors from medical scans. Team Name: M &H_lab_NU.",

keywords = "Head and neck, Multi-scale fusion, Tumor segmentation",

author = "Abhishek Srivastava and Debesh Jha and Bulent Aydogan and Abazeed, {Mohamed E.} and Ulas Bagci",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 3rd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, held in Conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022 ; Conference date: 22-09-2022 Through 22-09-2022",

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Srivastava, A, Jha, D, Aydogan, B, Abazeed, ME & Bagci, U 2023, Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation. in V Andrearczyk, V Oreiller, A Depeursinge & M Hatt (eds), Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13626 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 107-113, 3rd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, held in Conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022, Singapore, Singapore, 9/22/22. https://doi.org/10.1007/978-3-031-27420-6_11

Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation. / Srivastava, Abhishek; Jha, Debesh; Aydogan, Bulent et al.
Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings. ed. / Vincent Andrearczyk; Valentin Oreiller; Adrien Depeursinge; Mathieu Hatt. Springer Science and Business Media Deutschland GmbH, 2023. p. 107-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13626 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Srivastava A, Jha D, Aydogan B, Abazeed ME , Bagci U. Multi-scale Fusion Methodologies for Head and Neck Tumor Segmentation. In Andrearczyk V, Oreiller V, Depeursinge A, Hatt M, editors, Head and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 107-113. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-27420-6_11