MRI-guided Automated Delineation of Gross Tumor Volume for Nasopharyngeal Carcinoma using Deep Learning

Meiyan Yue, Zhenhui Dai, Jiahui He, Yaoqin Xie, Nazar Zaki, Wenjian Qin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a novel deep learning-based automatic delineation method of nasopharynx gross tumor volume (GTVnx) by combing computed tomography (CT) and magnetic resonance imaging (MRI) modalities. The purpose of this study is to explore whether MRI can provide additional information to improve the accuracy of delineation on CT. The proposed model can adaptively leverage the high contrast information of MRI into the automated delineation of GTVnx on CT in nasopharyngeal carcinoma (NPC) radiotherapy. In this study, the dataset collected from 192 patients with NPC was used to verify the performance of the proposed method. The average Dice Similarity Coefficient, 95% Hausdorff Distance and Average Symmetric Surface Distance of the segmentation results predicted by the proposed model are 0.7181, 9.6637mm, and 2.8014mm, respectively, which outperformed that of the single-modal and the concatenation-based multi-modal segmentation models.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE 35th International Symposium on Computer-Based Medical Systems, CBMS 2022
EditorsLinlin Shen, Alejandro Rodriguez Gonzalez, KC Santosh, Zhihui Lai, Rosa Sicilia, Joao Rafael Almeida, Bridget Kane
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages292-296
Number of pages5
ISBN (Electronic)9781665467704
DOIs
Publication statusPublished - 2022
Event35th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2022 - Shenzhen, China
Duration: Jul 21 2022Jul 23 2022

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
Volume2022-July
ISSN (Print)1063-7125

Conference

Conference35th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2022
Country/TerritoryChina
CityShenzhen
Period7/21/227/23/22

Keywords

  • deep learning
  • multi-modality
  • nasopharyngeal carcinoma
  • segmentation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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