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Diane M. Twickler
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2020 – today
- 2023
- [c7]James Huang, Quyen N. Do, Maysam Shahedi, Yin Xi, Matthew A. Lewis, Christina L. Herrera, David Owen, Catherine Y. Spong, Ananth J. Madhuranthakam, Diane M. Twickler, Baowei Fei:
Deep-learning-based automatic segmentation of the placenta and uterine cavity on prenatal MR images. Medical Imaging: Computer-Aided Diagnosis 2023 - [c6]James Huang, Maysam Shahedi
, Quyen N. Do, Yin Xi, Matthew A. Lewis, Christina L. Herrera, David Owen, Catherine Y. Spong, Ananth J. Madhuranthakam, Diane M. Twickler, Baowei Fei:
Topography-based feature extraction of the human placenta from prenatal MR images. Medical Imaging: Image Processing 2023 - 2022
- [c5]Maysam Shahedi
Automatic segmentation of uterine cavity and placenta on MR images using deep learning. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2022 - [c4]Ka'Toria N. Leitch, Maysam Shahedi, James D. Dormer, Quyen N. Do
Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features. Medical Imaging: Computer-Aided Diagnosis 2022 - [c3]James D. Dormer, Michael Villordon, Maysam Shahedi
CascadeNet for hysterectomy prediction in pregnant women due to placenta accreta spectrum. Medical Imaging: Image Processing 2022 - 2021
- [c2]Yin Xi
Assessing reproducibility in magnetic resonance (MR) radiomics features between deep-learning segmented and expert manual segmented data and evaluating their diagnostic performance in pregnant women with suspected placenta accreta spectrum (PAS). Medical Imaging: Computer-Aided Diagnosis 2021 - 2020
- [c1]Maysam Shahedi
Segmentation of uterus and placenta in MR images using a fully convolutional neural network. Medical Imaging: Computer-Aided Diagnosis 2020
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