Tomography

Displaying 1 - 6 of 6
Wang, S. J., Hu, Z., Li, C., He, X., Zhu, C., Wang, Y., Sattar, U., Bazojoo, V., He, H. Y. N., Blumenfeld, J. D., & Prince, M. R. (2024). Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning. Tomography, 10(7), 1148–1158. https://doi.org/10.3390/tomography10070087
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Santos, L., Hsu, H.-Y., Nelson, R. R., Sullivan, B., Shin, J., Fung, M., Lebel, M. R., Jambawalikar, S., & Jaramillo, D. (2024). Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions. Tomography, 10(4), 504–519. https://doi.org/10.3390/tomography10040039
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Zhu, C., Dev, H., Sharbatdaran, A., He, X., Shimonov, D., Chevalier, J. M., Blumenfeld, J. D., Wang, Y., Teichman, K., Shih, G., Goel, A., & Prince, M. R. (2023). Clinical Quality Control of MRI Total Kidney Volume Measurements in Autosomal Dominant Polycystic Kidney Disease. Tomography, 9(4), 1341–1355. https://doi.org/10.3390/tomography9040107
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Siddique, M., Liu, M., Duong, P., Jambawalikar, S., & Ha, R. (2023). Deep Learning Approaches with Digital Mammography for Evaluating Breast Cancer Risk, a Narrative Review. Tomography, 9(3), 1110–1119. https://doi.org/10.3390/tomography9030091
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Taskiran, N., Hiura, G., Zhang, X., Barr, R., Dashnaw, S., Hoffman, E., Malinsky, D., Oelsner, E., Prince, M., Smith, B., Sun, Y., Sun, Y., Wild, J., Shen, W., & Hughes, E. (2022). Mapping Alveolar Oxygen Partial Pressure in COPD Using Hyperpolarized Helium-3: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study. Tomography, 8(5), 2268–2284. https://doi.org/10.3390/tomography8050190
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Sharbatdaran, A., Romano, D., Teichman, K., Dev, H., Raza, S. I., Goel, A., Moghadam, M. C., Blumenfeld, J. D., Chevalier, J. M., Shimonov, D., Shih, G., Wang, Y., & Prince, M. R. (2022). Deep Learning Automation of Kidney, Liver, and Spleen Segmentation for Organ Volume Measurements in Autosomal Dominant Polycystic Kidney Disease. Tomography, 8(4), 1804–1819. https://doi.org/10.3390/tomography8040152
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