10 Results

People

  1. Veeraraghavan
    Veeraraghavan
  2. Deasy
    Deasy
  3. Jiang
    Jiang
  4. Tyagi
    Tyagi
  5. Hu
    Hu
  6. Rimner
    Rimner
  7. Berry
    Berry
  8. Cervino Arriba
    Cervino Arriba
  9. Crane
    Crane
  10. Lee
    Lee

Groups

  1. Medical Physics (10)
  2. Radiotherapy Physics Service (10)
  3. Sloan Kettering Institute Postdocs (10)
  4. Radiation Oncology, Department of (8)
  5. Graduate Medical Education (4)
  6. GME, Radiation Oncology (3)
  7. Center for Pancreatic Cancer Research (2)
  8. GME, Medical Physics (1)
  9. GME, Radiology (1)
  10. Multidisciplinary Brain Metastasis Program (1)
  1. "image segmentation"
  2. "Harini Veeraraghavan"
  3. "Radiotherapy Physics Service"
Formats
  1. Journal Article (8)
  2. Conference Paper (2)
Groups
  1. Medical Physics (10)
  2. Radiotherapy Physics Service (10)
  3. Sloan Kettering Institute Postdocs (10)
  4. Radiation Oncology, Department of (8)
  5. Graduate Medical Education (4)
  6. GME, Radiation Oncology (3)

More Groups

People
  1. Harini Veeraraghavan (10)
  2. Jue Jiang (8)
  3. Neelam Tyagi (8)
  4. Joseph Deasy (6)
  5. Yu-Chi Hu (5)
  6. Andreas Rimner (4)

More People

Years
  1. 2023 (2)
  2. 2022 (2)
  3. 2021 (1)
  4. 2020 (2)
  5. 2019 (3)
Publications
  1. Medical Physics (4)
  2. Lecture Notes in Computer Science (2)
  3. Physics in Medicine and Biology (2)
  4. IEEE Transactions on Medical Imaging (1)
  5. Radiotherapy and Oncology (1)
Publishers
  1. American Association of Physicists in Medicine (4)
  2. IOP Publishing Ltd (2)
  3. Springer (2)
  4. Elsevier Inc. (1)
  5. IEEE (1)

Results (10)


Citation style sort is year ascending, and then by author or title. Author ascending is default.
  • Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer
    Journal Article

    Simeth, J.; Jiang, J.; Nosov, A.; Wibmer, A.; Zelefsky, M.; Tyagi, N.; Veeraraghavan, H.
    Medical Physics (2023)

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  • Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT
    Journal Article

    Jiang, J.; Hong, J.; Tringale, K.; Reyngold, M.; Crane, C.; Tyagi, N.; Veeraraghavan, H.
    Medical Physics (2023)

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  • Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)
    Conference Paper

    Jiang, J.; Tyagi, N.; Tringale, K.; Crane, C.; Veeraraghavan, H.
    Springer (2022)

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  • Nested block self-attention multiple resolution residual network for multiorgan segmentation from CT
    Journal Article

    Jiang, J.; Elguindi, S.; Berry, S. L.; Onochie, I.; Cervino, L.; Deasy, J. O.; Veeraraghavan, H.
    Medical Physics (2022)

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  • Automatic segmentation of brain metastases using T1 magnetic resonance and computed tomography images
    Journal Article

    Hsu, D. G.; Ballangrud, Å.; Shamseddine, A.; Deasy, J. O.; Veeraraghavan, H.; Cervino, L.; Beal, K.; Aristophanous, M.
    Physics in Medicine and Biology (2021)

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  • PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation-based MRI segmentation
    Journal Article

    Jiang, J.; Hu, Y. C.; Tyagi, N.; Rimner, A.; Lee, N.; Deasy, J. O.; Berry, S.; Veeraraghavan, H.
    IEEE Transactions on Medical Imaging (2020)

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  • Self-derived organ attention for unpaired CT-MRI deep domain adaptation based MRI segmentation
    Journal Article

    Jiang, J.; Hu, Y. C.; Tyagi, N.; Wang, C.; Lee, N.; Deasy, J. O.; Sean, B.; Veeraraghavan, H.
    Physics in Medicine and Biology (2020)

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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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  • Segmenting lung tumors on longitudinal imaging studies via a patient-specific adaptive convolutional neural network
    Journal Article

    Wang, C.; Tyagi, N.; Rimner, A.; Hu, Y. C.; Veeraraghavan, H.; Li, G.; Hunt, M.; Mageras, G.; Zhang, P.
    Radiotherapy and Oncology (2019)

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