日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Critical review of partial volume correction methods in PET and SPECT imaging: benefits, pitfalls, challenges, and future outlook

PET和SPECT成像中部分容积校正方法的批判性综述:优势、缺陷、挑战和未来展望

Azimi, Mohammad Saber; Rahmim, Arman; Arabi, Hossein; Sanaat, Amirhossein; Zeraatkar, Navid; Bouchareb, Yassine; Liu, Chi; Alavi, Abass; King, Michael; Boellaard, Ronald; Zaidi, Habib

Conventional versus Monte Carlo SPECT reconstruction of Lu-177: Toward reduced bias and variance in quantitative imaging

Lu-177 的常规 SPECT 重建与蒙特卡罗 SPECT 重建:降低定量成像的偏差和方差

Polson, Lucas A; Esquinas, Pedro; Kurkowska, Sara; Li, Chenguang; Uribe, Carlos; Rahmim, Arman

Impact of partial volume correction on radiomics reproducibility in theranostic SPECT/CT imaging

部分容积校正对诊疗一体化SPECT/CT成像中放射组学可重复性的影响

Azimi, Mohammad Saber; Cheraghi, Maryam; Ghodsi Rad, Mohammad Ali; Bayat, Mohadeseh; Alhashim, Maryam; Dadgar, Habibollah; Alabedi, Mahmoud; Ibrahim, Nahid; Alwuhaib, Enas; Arabi, Hossein; Rahmim, Arman; Zaidi, Habib

From images to physics-based computational models to digital twins: a framework for personalized cancer therapies

从图像到基于物理的计算模型再到数字孪生:个性化癌症治疗框架

Moradi Kashkooli, Farshad; Zhan, Wenbo; Bhandari, Ajay; Yusufaly, Tahir I; Kolios, Michael C; Rahmim, Arman; Soltani, M

Should end-to-end deep learning replace handcrafted radiomics?

端到端深度学习是否应该取代手工放射组学?

Buvat, Irène; Dutta, Joyita; Jha, Abhinav K; Siegel, Eliot; Yousefirizi, Fereshteh; Rahmim, Arman; Bradshaw, Tyler

Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging: a comprehensive deep learning study

基于SPECT心肌灌注显像的人工智能辅助冠状动脉疾病诊断:一项综合深度学习研究

Hajianfar, Ghasem; Gharibi, Omid; Sabouri, Maziar; Mohebi, Mobin; Amini, Mehdi; Yasemi, Mohammad Javad; Chehreghani, Mohammad; Maghsudi, Mehdi; Mansouri, Zahra; Edalat-Javid, Mohammad; Valavi, Setareh; Bitarafan Rajabi, Ahmad; Salimi, Yazdan; Arabi, Hossein; Rahmim, Arman; Shiri, Isaac; Zaidi, Habib

Enhancing PRRT Outcome Prediction in Neuroendocrine Tumors: Aggregated Multi-Lesion PET Radiomics Incorporating Inter-Tumor Heterogeneity

提高神经内分泌肿瘤PRRT疗效预测:整合肿瘤间异质性的多病灶PET放射组学

Sabouri, Maziar; Hajianfar, Ghasem; Gharibi, Omid; Rafiei Sardouei, Alireza; Menda, Yusuf; Dundar, Ayca; Gadens Zamboni, Camila; Jain, Sanchay; Kruzer, Marc; Zaidi, Habib; Yousefirizi, Fereshteh; Rahmim, Arman; Shariftabrizi, Ahmad

Effectiveness of Artificial Intelligence Models in Predicting Lung Cancer Recurrence: A Gene Biomarker-Driven Review

人工智能模型在预测肺癌复发中的有效性:基于基因生物标志物的综述

Pourakbar, Niloufar; Motamedi, Alireza; Pashapour, Mahta; Sharifi, Mohammad Emad; Sharabiani, Seyedemad Seyedgholami; Fazlollahi, Asra; Abdollahi, Hamid; Rahmim, Arman; Rezaei, Sahar

Computer-Aided Detection (CADe) of Small Metastatic Prostate Cancer Lesions on 3D PSMA PET Volumes Using Multi-Angle Maximum Intensity Projections

利用多角度最大强度投影技术对三维PSMA PET图像上的小型转移性前列腺癌病灶进行计算机辅助检测(CADe)

Toosi, Amirhosein; Harsini, Sara; Divband, Ghasemali; Bénard, François; Uribe, Carlos F; Oviedo, Felipe; Dodhia, Rahul; Weeks, William B; Lavista Ferres, Juan M; Rahmim, Arman

Pre-Treatment PET Radiomics for Prediction of Disease-Free Survival in Cervical Cancer

宫颈癌治疗前PET放射组学预测无病生存期

Yousefirizi, Fereshteh; Hajianfar, Ghasem; Sabouri, Maziar; Holloway, Caroline; Tonseth, Pete; Alexander, Abraham; Yusufaly, Tahir I; Mell, Loren K; Harsini, Sara; Bénard, François; Zaidi, Habib; Uribe, Carlos; Rahmim, Arman