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Journal of Nuclear Medicine

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segmentation

  • The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [<sup>18</sup>F]FDG and [<sup>68</sup>Ga]Ga-PSMA in PET/CT
    You have access
    The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [18F]FDG and [68Ga]Ga-PSMA in PET/CT
    Cláudia S. Constantino, Francisco P.M. Oliveira, Marisa Machado, Susana Vinga and Durval C. Costa
    Journal of Nuclear Medicine May 1, 2025, 66 (5) 795-801; DOI: https://doi.org/10.2967/jnumed.124.269067
  • Need for Objective Task-Based Evaluation of Image Segmentation Algorithms for Quantitative PET: A Study with ACRIN 6668/RTOG 0235 Multicenter Clinical Trial Data
    Open Access
    Need for Objective Task-Based Evaluation of Image Segmentation Algorithms for Quantitative PET: A Study with ACRIN 6668/RTOG 0235 Multicenter Clinical Trial Data
    Ziping Liu, Joyce C. Mhlanga, Huitian Xia, Barry A. Siegel and Abhinav K. Jha
    Journal of Nuclear Medicine March 1, 2024, 65 (3) 485-492; DOI: https://doi.org/10.2967/jnumed.123.266018
  • aPROMISE: A Novel Automated PROMISE Platform to Standardize Evaluation of Tumor Burden in <sup>18</sup>F-DCFPyL Images of Veterans with Prostate Cancer
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    aPROMISE: A Novel Automated PROMISE Platform to Standardize Evaluation of Tumor Burden in 18F-DCFPyL Images of Veterans with Prostate Cancer
    Nicholas Nickols, Aseem Anand, Kerstin Johnsson, Johan Brynolfsson, Pablo Borreli, Neil Parikh, Jesus Juarez, Lida Jafari, Mattias Eiber and Matthew Rettig
    Journal of Nuclear Medicine February 1, 2022, 63 (2) 233-239; DOI: https://doi.org/10.2967/jnumed.120.261863
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    Intraprostatic Tumor Segmentation on PSMA PET Images in Patients with Primary Prostate Cancer with a Convolutional Neural Network
    Dejan Kostyszyn, Tobias Fechter, Nico Bartl, Anca L. Grosu, Christian Gratzke, August Sigle, Michael Mix, Juri Ruf, Thomas F. Fassbender, Selina Kiefer, Alisa S. Bettermann, Nils H. Nicolay, Simon Spohn, Maria U. Kramer, Peter Bronsert, Hongqian Guo, Xuefeng Qiu, Feng Wang, Christoph Henkenberens, Rudolf A. Werner, Dimos Baltas, Philipp T. Meyer, Thorsten Derlin, Mengxia Chen and Constantinos Zamboglou
    Journal of Nuclear Medicine June 1, 2021, 62 (6) 823-828; DOI: https://doi.org/10.2967/jnumed.120.254623
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    Quantitative Evaluation of Segmentation- and Atlas-Based Attenuation Correction for PET/MR on Pediatric Patients
    Ilja Bezrukov, Holger Schmidt, Sergios Gatidis, Frédéric Mantlik, Jürgen F. Schäfer, Nina Schwenzer and Bernd J. Pichler
    Journal of Nuclear Medicine July 1, 2015, 56 (7) 1067-1074; DOI: https://doi.org/10.2967/jnumed.114.149476
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    An SPM8-Based Approach for Attenuation Correction Combining Segmentation and Nonrigid Template Formation: Application to Simultaneous PET/MR Brain Imaging
    David Izquierdo-Garcia, Adam E. Hansen, Stefan Förster, Didier Benoit, Sylvia Schachoff, Sebastian Fürst, Kevin T. Chen, Daniel B. Chonde and Ciprian Catana
    Journal of Nuclear Medicine November 1, 2014, 55 (11) 1825-1830; DOI: https://doi.org/10.2967/jnumed.113.136341
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    MR-Based Attenuation Correction Methods for Improved PET Quantification in Lesions Within Bone and Susceptibility Artifact Regions
    Ilja Bezrukov, Holger Schmidt, Frédéric Mantlik, Nina Schwenzer, Cornelia Brendle, Bernhard Schölkopf and Bernd J. Pichler
    Journal of Nuclear Medicine October 1, 2013, 54 (10) 1768-1774; DOI: https://doi.org/10.2967/jnumed.112.113209
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