Wu, W. T., Lin, C. Y., Shu, Y. C., Chen, L. R., Özçakar, L. & Chang, K. V. Subacromial Motion Metrics in Painful Shoulder Impingement: A Dynamic Quantitative Ultrasonography Analysis. Arch Phys Med Rehabil 104, 260–269 (2023).

Article  PubMed  Google Scholar 

Wu, W. T., Lin, C. Y., Shu, Y. C., Shen, P. C., Lin, T. Y., Chang, K. V. & Özçakar, L. The Potential of Ultrasound Radiomics in Carpal Tunnel Syndrome Diagnosis: A Systematic Review and Meta-Analysis. Diagnostics 13, Preprint at https://doi.org/10.3390/diagnostics13203280 (2023)

Jha, A. K., Mithun, S., Jaiswar, V., Sherkhane, U. B., Purandare, N. C., Prabhash, K., Rangarajan, V., Dekker, A., Wee, L. & Traverso, A. Repeatability and reproducibility study of radiomic features on a phantom and human cohort. Sci Rep 11, (2021).

Traverso, A., Wee, L., Dekker, A. & Gillies, R. Repeatability and Reproducibility of Radiomic Features: A Systematic Review. Int J Radiat Oncol Biol Phys 102, 1143–1158 (2018).

Article  PubMed  PubMed Central  Google Scholar 

Kuang, M., Hu, H. T., Li, W., Chen, S. L. & Lu, X. Z. Articles That Use Artificial Intelligence for Ultrasound: A Reader’s Guide. Front Oncol 11, Preprint at https://doi.org/10.3389/fonc.2021.631813 (2021)

Klontzas, M. E. Radiomics feature reproducibility: The elephant in the room. Eur J Radiol 175, 111430 (2024).

Article  PubMed  Google Scholar 

Sansone, V., Maiorano, E., Galluzzo, A. & Pascale, V. Calcific tendinopathy of the shoulder: Clinical perspectives into the mechanisms, pathogenesis, and treatment. Orthop Res Rev 10, 63–72 Preprint at https://doi.org/10.2147/ORR.S138225 (2018)

Oliva, F., Via, A. G. & Maffulli, N. Physiopathology of intratendinous calcific deposition. BMC Med 10, Preprint at https://doi.org/10.1186/1741-7015-10-95 (2012)

Duron, L., Savatovsky, J., Fournier, L. & Lecler, A. Can we use radiomics in ultrasound imaging? Impact of preprocessing on feature repeatability. Diagn Interv Imaging 102, 659–667 (2021).

Article  PubMed  Google Scholar 

Van Griethuysen, J. J. M., Fedorov, A., Parmar, C., Hosny, A., Aucoin, N., Narayan, V., Beets-Tan, R. G. H., Fillion-Robin, J. C., Pieper, S. & Aerts, H. J. W. L. Computational radiomics system to decode the radiographic phenotype. Cancer Res 77, e104–e107 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Santinha, J., Pinto dos Santos, D., Laqua, F., Visser, J. J., Groot Lipman, K. B. W., Dietzel, M., Klontzas, M. E., Cuocolo, R., Gitto, S. & Akinci D’Antonoli, T. ESR Essentials: radiomics—practice recommendations by the European Society of Medical Imaging Informatics. Eur Radiol (2024). https://doi.org/10.1007/s00330-024-11093-9

Jia, Y., Yang, J., Zhu, Y., Wu, H., Duan, Y., Chen, K. & Nie, F. Ultrasound-based radiomics: current status, challenges and future opportunities. Med Ultrason 24, 451–460 (2022).

Article  PubMed  Google Scholar 

Beggs, I., Bianchi, S., Bueno, A., Cohen, M., Court-Payen, M., Grainger, A., Klauser, A., Martinoli, C., McNally, E., Peetrons, P., O’Connor, P. & Reijnierse, M. European Society of MusculoSkeletal Radiology Musculoskeletal Ultrasound Technical Guidelines I. Shoulder. Preprint at https://essr.org/content-essr/uploads/2016/10/shoulder.pdf (2016). Accessed 27 Jan 2025

Mustafa, W. A. & Abdul Kader, M. M. M. A Review of Histogram Equalization Techniques in Image Enhancement Application. in J Phys Conf Ser 1019, (Institute of Physics Publishing, 2018).

Dorfner, F. J., Vahldiek, J. L., Donle, L., Zhukov, A., Xu, L., Häntze, H., Makowski, M. R., Aerts, H. J. W. L., Proft, F., Rodriguez, V. R., Rademacher, J., Protopopov, M., Haibel, H., Diekhoff, T., Torgutalp, M., Adams, L. C., Poddubnyy, D. & Bressem, K. K. Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection. (2024). at <http://arxiv.org/abs/2405.07369>. Accessed 27 Jan 2025

Chutia, U., Tewari, A. S., Singh, J. P. & Raj, V. K. Classification of Lung Diseases Using an Attention-Based Modified DenseNet Model. Journal of Imaging Informatics in Medicine 37, 1625–1641 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Free-Astro Team. Contrast-Limited Adaptive Histogram Equalization (CLAHE). (2023). at <https://siril.readthedocs.io/it/latest/processing/clahe.html>. Accessed 27 Jan 2025

Shi, Z., Feng, Y., Zhao, M., Zhang, E. & He, L. Normalised gamma transformation-based contrast-limited adaptive histogram equalisation with colour correction for sand-dust image enhancement. IET Image Process 14, 747–756 (2020).

Article  Google Scholar 

Mat Radzi, S. F., Abdul Karim, M. K., Saripan, M. I., Abd Rahman, M. A., Osman, N. H., Dalah, E. Z. & Mohd Noor, N. Impact of Image Contrast Enhancement on Stability of Radiomics Feature Quantification on a 2D Mammogram Radiograph. IEEE Access 8, 127720–127731 (2020).

Article  Google Scholar 

Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Finet, J., Fillion-Robin, J. C., Pujol, S., Bauer, C., Jennings, D., Fennessy, F., Sonka, M., Buatti, J., Aylward, S., Miller, J. V., Pieper, S. & Kikinis, R. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 30, 1323–1341 (2012).

Article  PubMed  PubMed Central  Google Scholar 

Tejani, A. S., Klontzas, M. E., Gatti, A. A., Mongan, J. T., Moy, L., Park, S. H., Kahn, C. E. & CLAIM 2024 Update Panel, Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update. Radiol Artif Intell 6, (2024).

Kocak, B., Baessler, B., Bakas, S., Cuocolo, R., Fedorov, A., Maier-Hein, L., Mercaldo, N., Müller, H., Orlhac, F., Pinto dos Santos, D., Stanzione, A., Ugga, L. & Zwanenburg, A. CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII. Insights Imaging 14, (2023).

Ramli, Z., Farizan, A., Tamchek, N., Haron, Z. & Abdul Karim, M. K. Impact of Image Enhancement on the Radiomics Stability of Diffusion-Weighted MRI Images of Cervical Cancer. Cureus (2024). https://doi.org/10.7759/cureus.52132

Article  PubMed  PubMed Central  Google Scholar 

Zhang, Z., Ma, S., Liu, H. & Gong, Y. An edge detection approach based on directional wavelet transform. Computers and Mathematics with Applications 57, 1265–1271 (2009).

Article  Google Scholar 

Kolossváry, M., Jávorszky, N., Karády, J., Vecsey-Nagy, M., Dávid, T. Z., Simon, J., Szilveszter, B., Merkely, B. & Maurovich-Horvat, P. Effect of vessel wall segmentation on volumetric and radiomic parameters of coronary plaques with adverse characteristics. J Cardiovasc Comput Tomogr 15, 137–145 (2021).

Article  PubMed  Google Scholar 

Hu, G. qing, Ge, Y. qiong, Hu, X. kun & Wei, W. Predicting coronary artery calcified plaques using perivascular fat CT radiomics features and clinical risk factors. BMC Med Imaging 22, (2022).

Prinzi, F., Orlando, A., Gaglio, S. & Vitabile, S. Interpretable Radiomic Signature for Breast Microcalcification Detection and Classification. Journal of Imaging Informatics in Medicine 37, 1038–1053 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Huang, X., Wang, X., Liu, Y., Wang, Z., Li, S. & Kuang, P. Contrast-enhanced CT-based radiomics differentiate anterior mediastinum lymphoma from thymoma without myasthenia gravis and calcification. Clin Radiol 79, e500–e510 (2024).

Article  CAS  PubMed  Google Scholar 

Xu, M., Zeng, S., Li, F. & Liu, G. Utilizing grayscale ultrasound-based radiomics nomogram for preoperative identification of triple negative breast cancer. Radiologia Medica 129, 29–37 (2024).

Article  PubMed  Google Scholar 

Zhang, S., Hou, J., Xia, W., Zhao, Z., Xu, M., Li, S., Xu, C., Zhang, T. & Liu, W. Value of intralesional and perilesional radiomics for predicting the bioactivity of hepatic alveolar echinococcosis. Front Oncol 14, (2024).

Shi, Y., Zou, Y., Liu, J., Wang, Y., Chen, Y., Sun, F., Yang, Z., Cui, G., Zhu, X., Cui, X. & Liu, F. Ultrasound-based radiomics XGBoost model to assess the risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual application of SHAP. Front Oncol 12, (2022).

Yu, Y., Gao, G., Gao, X., Zhang, Z., He, Y., Shi, L. & Kang, Z. A study on the radiomic correlation between CBCT and pCT scans based on modified 3D-RUnet image segmentation. Front Oncol 14, (2024).