OtherAI/Advanced Image Analysis
Open Access
18F-FDG PET maximum intensity projections and artificial intelligence: a win-win combination to easily measure prognostic biomarkers in DLBCL patients
Kibrom Berihu Girum, Louis Rebaud, Anne-Ségolène Cottereau, Michel Meignan, Jérôme Clerc, Laetitia Vercellino, Olivier Casasnovas, Franck Morschhauser, Catherine Thieblemont and Irène Buvat
Journal of Nuclear Medicine June 2022, jnumed.121.263501; DOI: https://doi.org/10.2967/jnumed.121.263501
Kibrom Berihu Girum
1 LITO laboratory, UMR 1288 Inserm, Institut Curie, University Paris Saclay, France;
Louis Rebaud
2 LITO laboratory, UMR 1288 Inserm, Institut Curie, University Paris Saclay; Research and Clinical Collaborations, Siemens Medical Solutions USA, 810 Innovation Dr, Knoxville, TN 37932, United states, France;
Anne-Ségolène Cottereau
3 LITO laboratory, UMR 1288 Inserm, Institut Curie, University Paris-Saclay, Orsay, France; Department of Nuclear Medicine, Cochin Hospital, AP-HP, Paris Descartes University, Paris, France, France;
Michel Meignan
4 Lysa Imaging, Henri Mondor University Hospital, AP-HP, University Paris East, Creteil, France, France;
Jérôme Clerc
5 Department of Nuclear Medicine, Cochin Hospital, AP-HP, Paris Descartes University, Paris, France, France;
Laetitia Vercellino
6 Department of Nuclear Medicine, Saint-Louis Hospital, AP-HP, Paris, France, France;
Olivier Casasnovas
7 Department of Hematology, University Hospital of Dijon, Dijon, France, France;
Franck Morschhauser
8 Department of Hematology, Claude Huriez hospital, University Lille, EA 7365, Research Group on Injectable Forms and Associated Technologies, Lille, France, France;
Catherine Thieblemont
9 Department of Hematology, Saint Louis Hospital, AP-HP, Paris, France, France
Irène Buvat
1 LITO laboratory, UMR 1288 Inserm, Institut Curie, University Paris Saclay, France;
Data supplements
Supplemental Data
Files in this Data Supplement:
In this issue
Journal of Nuclear Medicine
Vol. 66, Issue 1
January 1, 2025
18F-FDG PET maximum intensity projections and artificial intelligence: a win-win combination to easily measure prognostic biomarkers in DLBCL patients
Kibrom Berihu Girum, Louis Rebaud, Anne-Ségolène Cottereau, Michel Meignan, Jérôme Clerc, Laetitia Vercellino, Olivier Casasnovas, Franck Morschhauser, Catherine Thieblemont, Irène Buvat
Journal of Nuclear Medicine Jun 2022, jnumed.121.263501; DOI: 10.2967/jnumed.121.263501
18F-FDG PET maximum intensity projections and artificial intelligence: a win-win combination to easily measure prognostic biomarkers in DLBCL patients
Kibrom Berihu Girum, Louis Rebaud, Anne-Ségolène Cottereau, Michel Meignan, Jérôme Clerc, Laetitia Vercellino, Olivier Casasnovas, Franck Morschhauser, Catherine Thieblemont, Irène Buvat
Journal of Nuclear Medicine Jun 2022, jnumed.121.263501; DOI: 10.2967/jnumed.121.263501
Jump to section
Related Articles
Cited By...
- Integration of clinical, pathological, radiological, and transcriptomic data improves the prediction of first-line immunotherapy outcome in metastatic non-small cell lung cancer
- Promising Candidate Prognostic Biomarkers in [18F]FDG PET Images: Evaluation in Independent Cohorts of Non-Small Cell Lung Cancer Patients
- Tumor Location Relative to the Spleen Is a Prognostic Factor in Lymphoma Patients: A Demonstration from the REMARC Trial