Application value of radiomics features based on PSMA PET/CT in diagnosis of clinically significant prostate cancer: a comparison between manual and automatic segmentation

Radiomics features from PSMA-PET/CT offer superior diagnostic performance for csPCa compared to SUVmax. The use of CNN-based segmentation facilitates the development of more efficient, objective, and stable radiomics models, with reduced inter-observer variability and improved reproducibility.

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Publication Details

Journal
BMC Medical Imaging
Published
2025-11-26
DOI
https://doi.org/10.1186/s12880-025-02064-7
Primary Topic
Prostate Cancer Treatment and Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Application value of radiomics features based on PSMA PET/CT in diagnosis of clinically significant prostate cancer: a comparison between manual and automatic segmentation

Kebing Li, Xiaofen Ma, Jingwen Li, Ming Zhang et al.
BMC Medical Imaging
Prostate Cancer Treatment and Research
article

Application value of radiomics features based on PSMA PET/CT in diagnosis of clinically significant prostate cancer: a comparison between manual and automatic segmentation

Kebing Li, Xiaofen Ma, Jingwen Li, Ming Zhang, Yujun Geng, Xinzhi Wang, Junzhang Tian
article en

Abstract

Radiomics features from PSMA-PET/CT offer superior diagnostic performance for csPCa compared to SUVmax. The use of CNN-based segmentation facilitates the development of more efficient, objective, and stable radiomics models, with reduced inter-observer variability and improved reproducibility.

BMC Medical ImagingVol. 25(1)
Jinan University (CN), Meizhou City People's Hospital (CN), Second Affiliated Hospital of Guangzhou Medical University (CN), Guangdong Provincial People's Hospital (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 45%
Prostate Cancer Treatment and Research
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Application value of radiomics features based on PSMA PET/CT in diagnosis of clinically significant prostate cancer: a comparison between manual and automatic segmentation — Kebing Li, Xiaofen Ma, et al. · BMC Medical Imaging (2025) | TGRS Research Map | TGRS