Synapse - Jue Jiang

Results (78)

Deep learning-based auto-segmentation of targets and organs-at-risk for magnetic resonance imaging only planning of prostate radiotherapy

Journal Article

Elguindi, S.; Zelefsky, M. J.; Jiang, J.; Veeraraghavan, H.; Deasy, J. O.; Hunt, M. A.; Tyagi, N.
Physics and Imaging in Radiation Oncology (2019)

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Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation

Conference Paper

Jue, J.; Jason, H.; Neelam, T.; Andreas, R.; Sean, B. L.; Joseph, D. O.; Harini, V.
Springer (2019)

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Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets

Journal Article

Jiang, J.; Hu, Y. C.; Tyagi, N.; Zhang, P.; Rimner, A.; Deasy, J. O.; Veeraraghavan, H.
Medical Physics (2019)

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Toward predicting the evolution of lung tumors during radiotherapy observed on a longitudinal MR imaging study via a deep learning algorithm

Journal Article

Wang, C.; Rimner, A.; Hu, Y. C.; Tyagi, N.; Jiang, J.; Yorke, E.; Riyahi, S.; Mageras, G.; Deasy, J. O.; Zhang, P.
Medical Physics (2019)

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Colonic polyp detection in endoscopic videos with single shot detection based deep Convolutional Neural Network

Journal Article

Liu, M.; Jiang, J.; Wang, Z.
IEEE Access (2019)

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Adaptively dense feature pyramid network for object detection

Journal Article

Pan, H.; Chen, G.; Jiang, J.
IEEE Access (2019)

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Self-attention based deep learning probabilistic parotid gland segmentation quality evaluation using dose volume histogram analysis

Meeting Abstract

Berry, S.; Jiang, J.; Elguindi, S.; Hunt, M.; Deasy, J.; Veeraraghavan, H.
Medical Physics (2019)

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Synthetic CTs generated by deep learning approaches: How good are they for radiomics analysis?

Meeting Abstract

Tixier, F.; Klages, P.; Riyahi, S.; Jiang, J.; Um, H.; Tyagi, N.; Young, R.; Veeraraghavan, H.
Medical Physics (2019)

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Longitudinal segmentation of parotid gland changes from MRI through unsupervised cross-modality deep learning through structure-specific appearance constraints

Meeting Abstract

Jiang, J.; Um, H.; Hu, Y.; Tyagi, N.; Wang, C.; Lee, N.; Deasy, J.; Berry, S.; Veeraraghavan, H.
Medical Physics (2019)

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Robustness of conditional generative adversarial networks in generating head and neck synthetic CT images for MR-only radiotherapy treatment planning

Meeting Abstract

Klages, P.; Benslimane, I.; Riyahi, S.; Jiang, J.; Hunt, M.; Deasy, J.; Veeraraghavan, H.; Tyagi, N.
Medical Physics (2019)

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