Skip to main content

Main menu

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • View or Listen to JNM Podcast
  • Visit JNM on Facebook
  • Join JNM on LinkedIn
  • Follow JNM on Twitter
  • Subscribe to our RSS feeds
Meeting ReportOncology, Basic and Translational - Technical Advances & Quantification (this would include image-guided diagnostics/therapy)

Automating Total Tumor Volume (TTV) generation on 177Lu-PSMA SPECT/CT using deep learning to create normal organs on the CT for automatic physiological uptake removal in patients with metastatic castration resistant prostate cancer (mCRPC)

Peter Wilson, Remy Niman, Timothy Susman, Sarennya Pathmanandavel, Louise Emmett and Aaron Nelson
Journal of Nuclear Medicine June 2023, 64 (supplement 1) P914;
Peter Wilson
1MIM Software Inc.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Remy Niman
2MIM Software, Inc
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Timothy Susman
1MIM Software Inc.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sarennya Pathmanandavel
3Department of Theranostics and Nuclear Medicine, St Vincent’s Hospital
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Louise Emmett
3Department of Theranostics and Nuclear Medicine, St Vincent’s Hospital
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Aaron Nelson
1MIM Software Inc.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
Loading

Article Figures & Data

Figures

  • Figure
    • Download figure
    • Open in new tab
    • Download powerpoint
  • Figure
    • Download figure
    • Open in new tab
    • Download powerpoint
Previous
Back to top

In this issue

Journal of Nuclear Medicine
Vol. 64, Issue supplement 1
June 1, 2023
  • Table of Contents
  • Index by author
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Automating Total Tumor Volume (TTV) generation on 177Lu-PSMA SPECT/CT using deep learning to create normal organs on the CT for automatic physiological uptake removal in patients with metastatic castration resistant prostate cancer (mCRPC)
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
Automating Total Tumor Volume (TTV) generation on 177Lu-PSMA SPECT/CT using deep learning to create normal organs on the CT for automatic physiological uptake removal in patients with metastatic castration resistant prostate cancer (mCRPC)
Peter Wilson, Remy Niman, Timothy Susman, Sarennya Pathmanandavel, Louise Emmett, Aaron Nelson
Journal of Nuclear Medicine Jun 2023, 64 (supplement 1) P914;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Automating Total Tumor Volume (TTV) generation on 177Lu-PSMA SPECT/CT using deep learning to create normal organs on the CT for automatic physiological uptake removal in patients with metastatic castration resistant prostate cancer (mCRPC)
Peter Wilson, Remy Niman, Timothy Susman, Sarennya Pathmanandavel, Louise Emmett, Aaron Nelson
Journal of Nuclear Medicine Jun 2023, 64 (supplement 1) P914;
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
  • Figures & Data
  • Info & Metrics

Related Articles

  • No related articles found.
  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • 68Ga-pentixather PET/CT for newly diagnosed multiple myeloma: Comparison to 68Ga-pentixafor PET/CT
  • Predicting Tumor Response to Neoadjuvant Chemotherapy based on Pretreatment 18F-FDG PET/CT and Clinical Parameters in Locally Advanced Oral Squamous Cell Carcinoma
  • Trial in Progress: Phase 1B Study of Personalized Ultrahypofractionated Stereotactic Ablative Radiotherapy of High-Risk Prostate Cancer Guided by PET PSMA (Gallium 68 gozetotide PSMA-11) response [PULSAR ProPhet]
Show more Oncology, Basic and Translational - Technical Advances & Quantification (this would include image-guided diagnostics/therapy)

Similar Articles

SNMMI

© 2025 SNMMI

Powered by HighWire