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Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks.

B. Saghafi, P. Garg, B. Wagner, S. Smith, J. Xu, A. Madhuranthakam, Y. Jung, J. Divers, B. Freedman, J. Maldjian, и A. Montillo. DLMIA/ML-CDS@MICCAI, том 10553 из Lecture Notes in Computer Science, стр. 151-159. Springer, (2017)

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Prabhanjan Ananth

Ananth Komanduri

Norbert J J Bock

Heinrich J J Mieschendahl

J J M Ramakers

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Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation.G. Murugesan, S. Nalawade, C. Yogananda, B. Wagner, F. Yu, B. Fei, A. Madhuranthakam, и J. Maldjian. BrainLes@MICCAI (2), том 11993 из Lecture Notes in Computer Science, стр. 148-157. Springer, (2019)Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features.K. Leitch, M. Shahedi, J. Dormer, Q. Do, Y. Xi, M. Lewis, C. Herrera, C. Spong, A. Madhuranthakam, D. Twickler и 1 other автор(ы). Medical Imaging: Computer-Aided Diagnosis, том 12033 из SPIE Proceedings, SPIE, (2022)Deep-learning-based automatic segmentation of the placenta and uterine cavity on prenatal MR images.J. Huang, Q. Do, M. Shahedi, Y. Xi, M. Lewis, C. Herrera, D. Owen, C. Spong, A. Madhuranthakam, D. Twickler и 1 other автор(ы). Medical Imaging: Computer-Aided Diagnosis, том 12465 из SPIE Proceedings, SPIE, (2023)CascadeNet for hysterectomy prediction in pregnant women due to placenta accreta spectrum.J. Dormer, M. Villordon, M. Shahedi, K. Leitch, Q. Do, Y. Xi, M. Lewis, A. Madhuranthakam, C. Herrera, C. Spong и 2 other автор(ы). Medical Imaging: Image Processing, том 12032 из SPIE Proceedings, SPIE, (2022)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).Y. Xi, M. Shahedi, Q. Do, J. Dormer, M. Lewis, B. Fei, C. Spong, A. Madhuranthakam, и D. Twickler. Medical Imaging: Computer-Aided Diagnosis, том 11597 из SPIE Proceedings, SPIE, (2021)Federated Learning for Brain Tumor Segmentation Using MRI and Transformers.S. Nalawade, C. Ganesh, B. Wagner, D. Reddy, Y. Das, F. Yu, B. Fei, A. Madhuranthakam, и J. Maldjian. BrainLes@MICCAI (2), том 12963 из Lecture Notes in Computer Science, стр. 444-454. Springer, (2021)Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks.B. Saghafi, P. Garg, B. Wagner, S. Smith, J. Xu, A. Madhuranthakam, Y. Jung, J. Divers, B. Freedman, J. Maldjian и 1 other автор(ы). DLMIA/ML-CDS@MICCAI, том 10553 из Lecture Notes in Computer Science, стр. 151-159. Springer, (2017)Segmentation of uterus and placenta in MR images using a fully convolutional neural network.M. Shahedi, J. Dormer, T. Devi, Q. Do, Y. Xi, M. Lewis, A. Madhuranthakam, D. Twickler, и B. Fei. Medical Imaging: Computer-Aided Diagnosis, том 11314 из SPIE Proceedings, SPIE, (2020)Automatic segmentation of uterine cavity and placenta on MR images using deep learning.M. Shahedi, J. Dormer, Q. Do, Y. Xi, M. Lewis, C. Herrera, C. Spong, A. Madhuranthakam, D. Twickler, и B. Fei. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, том 12036 из SPIE Proceedings, SPIE, (2022)Topography-based feature extraction of the human placenta from prenatal MR images.J. Huang, M. Shahedi, Q. Do, Y. Xi, M. Lewis, C. Herrera, D. Owen, C. Spong, A. Madhuranthakam, D. Twickler и 1 other автор(ы). Medical Imaging: Image Processing, том 12464 из SPIE Proceedings, SPIE, (2023)

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