Value of radiomics and deep learning feature fusion models based on dce-mri in distinguishing sinonasal squamous cell carcinoma from lymphoma

This study, by constructing a feature integration model combining radiomics and deep learning (DL), has demonstrated strong predictive capabilities in the preoperative non-invasive diagnosis of SNSCC and SNL, offering valuable information for tailoring personalized treatment plans for patients.

Authors

Yang Liu (ORCID: https://orcid.org/0000-0002-0857-9905)
Jianjun Zhang (ORCID: https://orcid.org/0000-0002-9853-3416)
Ziwei Zhang (ORCID: https://orcid.org/0000-0002-6194-2419)
Duo Zhang (ORCID: https://orcid.org/0000-0003-2497-4064)
Yunze Yang (ORCID: https://orcid.org/0000-0003-4776-4588)

Institutions

Chengde Medical University (CN)
Baoding People's Hospital (CN)

Publication Details

Journal: Frontiers in Oncology
Published: 2024-11-21
DOI: https://doi.org/10.3389/fonc.2024.1489973
Citations: 5
Primary Topic: Radiomics and Machine Learning in Medical Imaging
Type: article
Field-Weighted Citation Impact: 2.02

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article

Value of radiomics and deep learning feature fusion models based on dce-mri in distinguishing sinonasal squamous cell carcinoma from lymphoma

Yang Liu, Jianjun Zhang, Ziwei Zhang, Duo Zhang et al.

Nov 21, 2024

5 citations

Frontiers in Oncology

Radiomics and Machine Learning in Medical Imaging

2.02

article

Value of radiomics and deep learning feature fusion models based on dce-mri in distinguishing sinonasal squamous cell carcinoma from lymphoma

Yang Liu, Jianjun Zhang, Ziwei Zhang, Duo Zhang, Yunze Yang

November 21, 2024article en

5 citations

Abstract

This study, by constructing a feature integration model combining radiomics and deep learning (DL), has demonstrated strong predictive capabilities in the preoperative non-invasive diagnosis of SNSCC and SNL, offering valuable information for tailoring personalized treatment plans for patients.

Frontiers in OncologyVol. 14

Chengde Medical University (CN), Baoding People's Hospital (CN)

Peace, Justice and strong institutions

Openalex Percentile: Top 13%

Radiomics and Machine Learning in Medical Imaging

2.02

DOI Open Access PDF OpenAlex

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Value of radiomics and deep learning feature fusion models based on dce-mri in distinguishing sinonasal squamous cell carcinoma from lymphoma — Yang Liu, Jianjun Zhang, et al. · Frontiers in Oncology (2024) | TGRS Research Map | TGRS