International Journal of Cancer Management
The Official Journal of Cancer Research Center (CRC), Shahid Beheshti University of Medical Sciences
Scopus by Title (Ref)
1. Automatic Classification of Thyroid Nodules in Ultrasound Images using MobileNetV2-MSVM Hybrid Model
- Luong D.T. , et al.
2. CT-based texture analysis predicts BRAFV600E mutation in calcified papillary thyroid carcinoma
- Chen Y. , et al.
3. Differential diagnosis of thyroid nodules using heterogeneity quantification software on ultrasound images: correlation with the Bethesda system and surgical pathology
- Ryu Y.J. , et al.
4. A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images
- Yadav N. , et al.
5. The Application of Artificial Intelligence in Thyroid Nodules: A Systematic Review Based on Bibliometric Analysis
- Peng Y. , et al.
6. A contemporary review on soft computing techniques for thyroid identification and detection
- Srivastava R. , et al.
7. Artificial intelligence in thyroid ultrasound
- Cao C.L. , et al.
8. Radiomic Detection of Malignancy within Thyroid Nodules Using Ultrasonography—A Systematic Review and Meta-Analysis
- Cleere E.F. , et al.
9. Texture and shape analysis of diffusion-weighted imaging for thyroid nodules classification using machine learning
- Sharafeldeen A. , et al.
10. Automated Breast Volume Scanner (ABVS)-Based Radiomic Nomogram: A Potential Tool for Reducing Unnecessary Biopsies of BI-RADS 4 Lesions
- Wang S.J. , et al.
11. Computer Techniques for Medical Image Classification: A Review
- Adebisi O.A. , et al.
12. Texture Analysis of Liver Ultrasound Images
- Yadav N. , et al.
13. A hybrid model for the identification and classification of thyroid nodules in medical ultrasound images
- Srivastava R. , et al.
14. Value of Quantitative CTTA in Differentiating Malignant from Benign Bosniak III Renal Lesions on CT Images
- Zhang Y. , et al.
15. Radiomics score combined with acr ti-rads in discriminating benign and malignant thyroid nodules based on ultrasound images: A retrospective study
- Luo P. , et al.
16. Ultrasound image classification of thyroid nodules using machine learning techniques
- Vadhiraj V.V. , et al.
17. Feasibility of the quantitative assessment method for ct quality control in phantom image evaluation
- Lee K.B. , et al.
18. CT texture analysis in differentiating benign and malignant thyroid nodules and predicting lymph node metastasis
- Chen J. , et al.
20. The diagnostic efficiency of ultrasound computer–aided diagnosis in differentiating thyroid nodules: A systematic review and narrative synthesis
- Chambara N. , et al.
21. Update on thyroid ultrasound: A narrative review from diagnostic criteria to artificial intelligence techniques
- Liang X.W. , et al.
22. CAD system based on B-mode and color Doppler sonographic features may predict if a thyroid nodule is hot or cold
- Abbasian Ardakani A. , et al.
23. Extreme learning machine for thyroid nodule classification with graph cluster ant colony optimization based feature selection
- Rasheeduddin S. , et al.