Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion

Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion

ObjectiveTo evaluate the performance of 2D and 3D radiomics features with different machine learning approaches to classify SPLs based on magnetic resonance(MR) T2 weighted imaging (T2WI).Material and MethodsA total of 132 patients with pathologically confirmed SPLs were examined and randomly divide...

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Détails bibliographiques
Auteurs principaux: Qi Wan, Jiaxuan Zhou, Xiaoying Xia, Jianfeng Hu, Peng Wang, Yu Peng, Tianjing Zhang, Jianqing Sun, Yang Song, Guang Yang, Xinchun Li
Format: article
Langue:EN
Publié: Frontiers Media S.A. 2021
Sujets:
algorithms
area under the curve
lung neoplasms
machine learning
magnetic resonance imaging
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Accès en ligne:https://doaj.org/article/d748289ae43d4287b7f74c3afaee95e4
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https://doaj.org/article/d748289ae43d4287b7f74c3afaee95e4

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