85 Results

People

  1. Do
    Do
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    Jiang
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    Deasy
  4. Eskreis-Winkler
    Eskreis-Winkler
  5. Stember
    Stember
  6. Wang
    Wang
  7. Rimner
    Rimner
  8. Veeraraghavan
    Veeraraghavan
  9. Apte
    Apte
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    Chakraborty

Groups

  1. Sloan Kettering Institute Postdocs (34)
  2. Medical Physics (30)
  3. Radiology, Department of (20)
  4. Body Imaging Service (14)
  5. Department of Medicine (14)
  6. Dermatology Service (11)
  7. Dermatology (11)
  8. Division of Subspecialty Medicine (11)
  9. Population Sciences Research Program (7)
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  1. "convolutional neural network"
Formats
  1. Journal Article (53)
  2. Conference Paper (24)
  3. Review (5)
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  5. Editorial (1)
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Groups
  1. Sloan Kettering Institute Postdocs (34)
  2. Medical Physics (30)
  3. Radiology, Department of (20)
  4. Body Imaging Service (14)
  5. Department of Medicine (14)
  6. Dermatology (11)

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People
  1. Kinh Gian Do (8)
  2. Jue Jiang (7)
  3. Joseph Deasy (5)
  4. Joseph Stember (5)
  5. Katja Pinker-Domenig (5)
  6. Sarah Eskreis-Winkler (5)

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Years
  1. 2025 (10)
  2. 2024 (17)
  3. 2023 (14)
  4. 2022 (5)
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Publications
  1. Medical Physics (11)
  2. Lecture Notes in Computer Science (6)
  3. Progress in Biomedical Optics and Imaging - Proceedings of SPIE (5)
  4. Proceedings of SPIE (4)
  5. Academic Radiology (2)
  6. Annals of Surgical Oncology (2)

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Publishers
  1. Springer (13)
  2. American Association of Physicists in Medicine (11)
  3. SPIE (11)
  4. IEEE (9)
  5. Elsevier Inc. (5)
  6. Elsevier Science, Inc. (4)

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Results (85)


Citation style sort is year ascending, and then by author or title. Author ascending is default.
  • Quantitative and qualitative evaluation of convolutional neural networks with a deeper U-net for sparse-view computed tomography reconstruction
    Journal Article

    Nakai, H.; Nishio, M.; Yamashita, R.; Ono, A.; Nakao, K. K.; Fujimoto, K.; Togashi, K.
    Academic Radiology (2020)

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  • Technical note: 3D localization of lung tumors on cone beam CT projections via a convolutional recurrent neural network
    Journal Article

    Wang, C.; Hunt, M.; Zhang, L.; Rimner, A.; Yorke, E.; Lovelock, M.; Li, X.; Li, T.; Mageras, G.; Zhang, P.
    Medical Physics (2020)

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  • Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: A pilot study
    Journal Article

    Yamashita, R.; Mittendorf, A.; Zhu, Z.; Fowler, K. J.; Santillan, C. S.; Sirlin, C. B.; Bashir, M. R.; Do, R. K. G.
    Abdominal Radiology (2020)

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  • GRASP-Pro: imProving GRASP DCE-MRI through self-calibrating subspace-modeling and contrast phase automation
    Journal Article

    Feng, L.; Wen, Q.; Huang, C.; Tong, A.; Liu, F.; Chandarana, H.
    Magnetic Resonance in Medicine (2020)

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  • A deep adaptive convolutional network for brain tumor segmentation from multimodal MR images
    Conference Paper

    Ghosal, P.; Reddy, S.; Sai, C.; Pandey, V.; Chakraborty, J.; Nandi, D.
    IEEE (2019)

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  • Mitigating inherent noise in Monte Carlo dose distributions using dilated U-Net
    Journal Article

    Javaid, U.; Souris, K.; Dasnoy, D.; Huang, S.; Lee, J. A.
    Medical Physics (2019)

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  • Cardio-pulmonary substructure segmentation of CT images using convolutional neural networks
    Conference Paper

    Haq, R.; Hotca, A.; Apte, A.; Rimner, A.; Deasy, J. O.; Thor, M.
    Springer (2019)

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  • Distinguish chromophobe renal cell carcinoma and renal oncocytoma based on analysis of multiphoton microscopic images using convolutional neural network
    Conference Paper

    Icaza, M.; Judd, N.; Jain, M.; Mukherjee, S.; Wu, B. L.
    SPIE (2019)

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  • Brain tumor classification using ResNet-101 based squeeze and excitation deep neural network
    Conference Paper

    Ghosal, P.; Nandanwar, L.; Kanchan, S.; Bhadra, A.; Chakraborty, J.; Nandi, D.
    IEEE (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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