Fully Automated Detection and Segmentation Pipeline for the Bone Marrow of the Lytic Bone of Multiple Myeloma Patients-Reference-Cited by-同舟云学术

Fully Automated Detection and Segmentation Pipeline for the Bone Marrow of the Lytic Bone of Multiple Myeloma Patients

Published:2023-12-07 Issue: Volume: Page:39-40
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Container-title:2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
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Author:

Koutoulakis Emmanouil¹,Trivizakis Eleftherios¹,Koutoulidis Vassilis²,Moulopoulos Lia A.²,Terpos Evangelos³,Ntanasis-Stathopoulos Ioannis³,Malandrakis Panagiotis³,Grigoropoulos Panagiotis²,Papadopoulos Panagiotis²,Nikiforaki Katerina¹,Papanikolaou Nickolas⁴,Fotiadis Dimitrios I.⁵,Marias Kostas¹

Affiliation:

1. Foundation for Research and Technology – Hellas,Heraklion,Greece

2. National Kapodistrian University of Athens,School of Medicine, Aretaieion Hospital,1st Department of Radiology,Athens,Greece

3. National and Kapodistrian University of Athens,School of Medicine,Department of Clinical Therapeutics,Athens,Greece

4. Champalimaud Foundation,Centre of the Unknown,Computational Clinical Imaging Group,Lisbon,Portugal

5. University of Ioannina,Unit of Medical Technology and Intelligent Information Systems,Department of MaterialsScience and Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10404092/10404107/10405013.pdf?arnumber=10405013

Reference9 articles.

1. Whole-Body Imaging of Multiple Myeloma: Diagnostic Criteria

2. Patterns of Multiple Myeloma During the Past 5 Decades: Stable Incidence Rates for All Age Groups in the Population but Rapidly Changing Age Distribution in the Clinic

3. Trends in Multiple Myeloma Incidence in the United States (US): Demographic and Geographic Considerations and Focus on Young Adults

4. Can multiple myeloma become a curable disease?

5. Deep Learning-Based CT Imaging in Diagnosing Myeloma and Its Prognosis Evaluation