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Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.
Jiang, Jue; Hu, Yu-Chi; Tyagi, Neelam; Zhang, Pengpeng; Rimner, Andreas; Deasy, Joseph O; Veeraraghavan, Harini.
Affiliation
  • Jiang J; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
  • Hu YC; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
  • Tyagi N; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
  • Zhang P; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
  • Rimner A; Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
  • Deasy JO; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
  • Veeraraghavan H; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
Med Phys ; 46(10): 4392-4404, 2019 Oct.
Article in En | MEDLINE | ID: mdl-31274206
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Magnetic Resonance Imaging / Tomography, X-Ray Computed / Multimodal Imaging / Deep Learning / Lung Neoplasms Limits: Humans Language: En Journal: Med Phys Year: 2019 Document type: Article Affiliation country: United States
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Magnetic Resonance Imaging / Tomography, X-Ray Computed / Multimodal Imaging / Deep Learning / Lung Neoplasms Limits: Humans Language: En Journal: Med Phys Year: 2019 Document type: Article Affiliation country: United States