Segmentation of Intraoperative 3D Ultrasound Images Using a Pyramidal Blur-Pooled 2D U-Net
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-27324-7_9
Reference13 articles.
1. Dixon, L., Lim, A., Grech-Sollars, M., Nandi, D., Camp, S.: Intraoperative ultrasound in brain tumor surgery: A review and implementation guide. Neurosurg. Rev. 45(4), 2503–2515 (2022)
2. Xiao, Y., Fortin, M., Unsgärd, G., Rivaz, H., Reinertsen, I.: REtroSpective Evaluation of Cerebral Tumors (RESECT): A clinical database of pre-operative MRI and intra-operative ultrasound in low-grade glioma surgeries: A. Med. Phys. 44(7), 3875–3882 (2017)
3. Behboodi, B., et al.: RESECT-SEG: Open access annotations of intra-operative brain tumor ultrasound images. (2022)
4. Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. Lect. Notes Comput. Sci. 9351, 234–241 (2015)
5. Sharifzadeh, M., Benali, H., Rivaz, H.: Investigating Shift Variance of Convolutional Neural Networks in Ultrasound Image Segmentation. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 69(5), 1703–1713 (2022)
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