Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach

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Samenvatting

Delineation of Gross Tumor Volume (GTV) is essential for the treatment of cancer with radiotherapy. GTV contouring is a time-consuming specialized manual task performed by radiation oncologists. Deep Learning (DL) algorithms have shown potential in creating automatic segmentations, reducing delineation time and inter-observer variation. The aim of this work was to create automatic segmentations of primary tumors (GTVp) and pathological lymph nodes (GTVn) in oropharyngeal cancer patients using DL. The organizers of the HECKTOR 2022 challenge provided 3D Computed Tomography (CT) and Positron Emission Tomography (PET) scans with ground-truth GTV segmentations acquired from nine different centers. Bounding box cropping was applied to obtain an anatomic based region of interest. We used the Swin UNETR model in combination with transfer learning. The Swin UNETR encoder weights were initialized by pre-trained weights of a self-supervised Swin UNETR model. An average Dice score of 0.656 was achieved on a test set of 359 patients from the HECKTOR 2022 challenge. Code is available at: https://github.com/HC94/swin_unetr_hecktor_2022.

Originele taal-2English
TitelHead and Neck Tumor Segmentation and Outcome Prediction - 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings
RedacteurenVincent Andrearczyk, Valentin Oreiller, Adrien Depeursinge, Mathieu Hatt
UitgeverijSpringer Science and Business Media Deutschland GmbH
Pagina's114-120
Aantal pagina's7
ISBN van geprinte versie9783031274190
DOI's
StatusPublished - 2023
Evenement3rd 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
Duur: 22-sep.-202222-sep.-2022

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13626 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Conference

Conference3rd 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
Land/RegioSingapore
StadSingapore
Periode22/09/202222/09/2022

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