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Intranodular and perinodular ultrasound radiomics distinguishes benign and malignant thyroid nodules: a multicenter study.

Xuelin Zhu | Jing Li | Hao Li | Kaifeng Wang | Jian Zhang | Jian Meng | Rong Wu | Meilan Zhang | Hai Du
Gland surgery | 2024

Ultrasound based radiomics prediction model can improve the differentiation ability of benign and malignant thyroid nodules to avoid overtreatment. This study evaluates the role of predictive models based on intranodular and perinodular ultrasound radiomics in distinguishing between benign and malignant thyroid nodules.

Pubmed ID: 39822358

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This is a list of tools and resources that we have found mentioned in this publication.


ITK-SNAP (tool)

RRID:SCR_002010

Open source interactive software application for three dimentional medical images, manual delineation of anatomical regions of interest, and performing automatic image segmentation. Used for delineating anatomical structures and regions in MRI, CT and other 3D biomedical imaging data.

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scikit-learn (tool)

RRID:SCR_002577

scikit-learn: machine learning in Python

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