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Journal of Nuclear Medicine

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deep learning

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    Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study
    Jaewon Yang, Luyao Shi, Rui Wang, Edward J. Miller, Albert J. Sinusas, Chi J. Liu, Grant T. Gullberg and Youngho Seo
    Journal of Nuclear Medicine February 26, 2021, jnumed.120.256396; DOI: https://doi.org/10.2967/jnumed.120.256396
  • Deep-Learning <sup>18</sup>F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma
    Open Access
    Deep-Learning 18F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma
    Nicolò Capobianco, Michel Meignan, Anne-Ségolène Cottereau, Laetitia Vercellino, Ludovic Sibille, Bruce Spottiswoode, Sven Zuehlsdorff, Olivier Casasnovas, Catherine Thieblemont and Irène Buvat
    Journal of Nuclear Medicine January 1, 2021, 62 (1) 30-36; DOI: https://doi.org/10.2967/jnumed.120.242412
  • Open Access
    Conditional Generative Adversarial Networks (cGANs) aided motion correction of dynamic 18F-FDG PET brain studies
    Lalith Kumar Shiyam Sundar, David Iommi, Otto Muzik, Zacharias Chalampalakis, Eva-Maria Klebermass, Marius Hienert, Lucas Rischka, Rupert Lanzenberger, Andreas Hahn, Ekaterina Pataraia, Tatjana Traub-Weidinger and Thomas Beyer
    Journal of Nuclear Medicine November 27, 2020, jnumed.120.248856; DOI: https://doi.org/10.2967/jnumed.120.248856
  • You have access
    Projection Space Implementation of Deep Learning–Guided Low-Dose Brain PET Imaging Improves Performance over Implementation in Image Space
    Amirhossein Sanaat, Hossein Arabi, Ismini Mainta, Valentina Garibotto and Habib Zaidi
    Journal of Nuclear Medicine September 1, 2020, 61 (9) 1388-1396; DOI: https://doi.org/10.2967/jnumed.119.239327
  • You have access
    Artificial Intelligence in Nuclear Medicine
    Felix Nensa, Aydin Demircioglu and Christoph Rischpler
    Journal of Nuclear Medicine September 1, 2019, 60 (Supplement 2) 29S-37S; DOI: https://doi.org/10.2967/jnumed.118.220590
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    Radiomics: Data Are Also Images
    Mathieu Hatt, Catherine Cheze Le Rest, Florent Tixier, Bogdan Badic, Ulrike Schick and Dimitris Visvikis
    Journal of Nuclear Medicine September 1, 2019, 60 (Supplement 2) 38S-44S; DOI: https://doi.org/10.2967/jnumed.118.220582
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    Generation of PET Attenuation Map for Whole-Body Time-of-Flight 18F-FDG PET/MRI Using a Deep Neural Network Trained with Simultaneously Reconstructed Activity and Attenuation Maps
    Donghwi Hwang, Seung Kwan Kang, Kyeong Yun Kim, Seongho Seo, Jin Chul Paeng, Dong Soo Lee and Jae Sung Lee
    Journal of Nuclear Medicine August 1, 2019, 60 (8) 1183-1189; DOI: https://doi.org/10.2967/jnumed.118.219493
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    Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study
    Julian Betancur, Lien-Hsin Hu, Frederic Commandeur, Tali Sharir, Andrew J. Einstein, Mathews B. Fish, Terrence D. Ruddy, Philipp A. Kaufmann, Albert J. Sinusas, Edward J. Miller, Timothy M. Bateman, Sharmila Dorbala, Marcelo Di Carli, Guido Germano, Yuka Otaki, Joanna X. Liang, Balaji K. Tamarappoo, Damini Dey, Daniel S. Berman and Piotr J. Slomka
    Journal of Nuclear Medicine May 1, 2019, 60 (5) 664-670; DOI: https://doi.org/10.2967/jnumed.118.213538
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    Synthesis of Patient-Specific Transmission Data for PET Attenuation Correction for PET/MRI Neuroimaging Using a Convolutional Neural Network
    Karl D. Spuhler, John Gardus, Yi Gao, Christine DeLorenzo, Ramin Parsey and Chuan Huang
    Journal of Nuclear Medicine April 1, 2019, 60 (4) 555-560; DOI: https://doi.org/10.2967/jnumed.118.214320
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    Dixon-VIBE Deep Learning (DIVIDE) Pseudo-CT Synthesis for Pelvis PET/MR Attenuation Correction
    Angel Torrado-Carvajal, Javier Vera-Olmos, David Izquierdo-Garcia, Onofrio A. Catalano, Manuel A. Morales, Justin Margolin, Andrea Soricelli, Marco Salvatore, Norberto Malpica and Ciprian Catana
    Journal of Nuclear Medicine March 1, 2019, 60 (3) 429-435; DOI: https://doi.org/10.2967/jnumed.118.209288

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