Automatic detection and segmentation of lesions in 18F-FDG PET/CT imaging of patients with Hodgkin lymphoma using 3D dense U-Net

This study demonstrates that the integration of U-Net and DenseNet architectures, along with the Tversky loss function, can significantly enhance the accuracy of Hodgkin lymphoma segmentation in PET/CT images compared to similar studies.

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Publication Details

Journal
Nuclear Medicine Communications
Published
2024-09-03
DOI
https://doi.org/10.1097/mnm.0000000000001892
Primary Topic
Medical Imaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Automatic detection and segmentation of lesions in 18F-FDG PET/CT imaging of patients with Hodgkin lymphoma using 3D dense U-Net

Parham Geramifar, Babak Nikkholgh, Rezvan Samimi, Zeinab Paymani et al.
Nuclear Medicine Communications
Medical Imaging Techniques and Applications
article

Automatic detection and segmentation of lesions in 18F-FDG PET/CT imaging of patients with Hodgkin lymphoma using 3D dense U-Net

Parham Geramifar, Babak Nikkholgh, Rezvan Samimi, Zeinab Paymani, Nafiseh Alemohammad, Ali Salimi, Roya Eisazadeh, Zaynab Sabouri, Mohammad Amin Izadi
article en

Abstract

This study demonstrates that the integration of U-Net and DenseNet architectures, along with the Tversky loss function, can significantly enhance the accuracy of Hodgkin lymphoma segmentation in PET/CT images compared to similar studies.

Nuclear Medicine CommunicationsVol. 45(11)
Shahed University (IR), GTx (United States) (US), University of Tehran (IR), Medical Center Hospital (US), Shariati Hospital (IR), Khatam University (IR), Shahid Beheshti University (IR), Tehran University of Medical Sciences (IR), University of Birmingham (GB)
Openalex Percentile: Top 76%
Medical Imaging Techniques and Applications
DOISourceOpenAlex
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Automatic detection and segmentation of lesions in 18F-FDG PET/CT imaging of patients with Hodgkin lymphoma using 3D dense U-Net — Parham Geramifar, Babak Nikkholgh, et al. · Nuclear Medicine Communications (2024) | TGRS Research Map | TGRS