Improving Automatic Renal Segmentation in Clinically Normal and Abnormal Paediatric DCE-MRI via Contrast Maximisation and Convolutional Networks for Computing Markers of Kidney Function
Asaturyan, H.; Villarini, B.; Sarao, K.; Chow, J.S.; Afacan, O.; Kurugol, S. Improving Automatic Renal Segmentation in Clinically Normal and Abnormal Paediatric DCE-MRI via Contrast Maximisation and Convolutional Networks for Computing Markers of Kidney Function. Sensors 2021, 21, 7942. https://doi.org/10.3390/s21237942
Asaturyan H, Villarini B, Sarao K, Chow JS, Afacan O, Kurugol S. Improving Automatic Renal Segmentation in Clinically Normal and Abnormal Paediatric DCE-MRI via Contrast Maximisation and Convolutional Networks for Computing Markers of Kidney Function. Sensors. 2021; 21(23):7942. https://doi.org/10.3390/s21237942
Chicago/Turabian StyleAsaturyan, Hykoush, Barbara Villarini, Karen Sarao, Jeanne S. Chow, Onur Afacan, and Sila Kurugol. 2021. "Improving Automatic Renal Segmentation in Clinically Normal and Abnormal Paediatric DCE-MRI via Contrast Maximisation and Convolutional Networks for Computing Markers of Kidney Function" Sensors 21, no. 23: 7942. https://doi.org/10.3390/s21237942