Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images

Alessia De Biase*, Wei Tang, Nikos Sourlos, Baoqiang Ma, Jiapan Guo, Nanna Maria Sijtsema, Peter van Ooijen

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

4 Citaten (Scopus)
86 Downloads (Pure)

Samenvatting

One of the primary treatment options for head and neck cancer is (chemo)radiation. Accurate delineation of the contour of the tumors is of great importance in the successful treatment of the tumor and in the prediction of patient outcomes. With this paper we take part in the HECKTOR 2021 challenge and we propose our methods for automatic tumor segmentation on PET and CT images of oropharyngeal cancer patients. To achieve this goal, we investigated different deep learning methods with the purpose of highlighting relevant image and modality related features, to refine the contour of the primary tumor. More specifically, we tested a Co-learning method [1] and a 3D Skip Spatial and Channel Squeeze and Excitation Multi-Scale Attention method (Skip-scSE-M), on the challenge dataset. The best results achieved on the test set were 0.762 mean Dice Similarity Score and 3.143 median of the Hausdorf Distance at 95 %.

Originele taal-2English
TitelHead and Neck Tumor Segmentation and Outcome Prediction - 2nd Challenge, HECKTOR 2021, Held in Conjunction with MICCAI 2021, Proceedings
RedacteurenVincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, Adrien Depeursinge
UitgeverijSpringer Science and Business Media Deutschland GmbH
Pagina's109-120
Aantal pagina's12
ISBN van geprinte versie9783030982522
DOI's
StatusPublished - 2022
Evenement2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021 - Virtual, Online
Duur: 27-sep.-202127-sep.-2021

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13209 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Conference

Conference2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021
StadVirtual, Online
Periode27/09/202127/09/2021

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