Monte Carlo assessment of time-of-flight benefits on the LYSO-based discovery RX PET/CT scanner. - Parham Geramifar; Mohammad Reza Ay; Mojtaba Shamsaei Zafarghandi; George Loudos; Arman Rahmim (ISBI, 2008)

Analytic system matrix resolution modeling in PET: An application to Rb-82 cardiac imaging. - Arman Rahmim; Martin A. Lodge; Jing Tang 005; Sahel Lashkari; Mohammad Reza Ay (ISBI, 2008)

Comparative assessment of different energy mapping methods for generation of 511-keV attenuation map from CT images in PET/CT systems: A phantom study. - Maryam Shirmohammad; Mohammad Reza Ay; Saeed Sarkar; Hossein Ghadiri; Arman Rahmim (ISBI, 2008)

Bayesian PET image reconstruction incorporating anato-functional joint entropy. - Jing Tang 005; Benjamin M. W. Tsui; Arman Rahmim (ISBI, 2008)

Accurate Event-Driven Motion Compensation in High-Resolution PET Incorporating Scattered and Random Events. - Arman Rahmim; Katie Dinelle; Ju-Chieh Cheng; Mikhail A. Shilov; William Paul Segars; Sarah C. Lidstone; Stephan Blinder; Olivier G. Rousset; Hamid Vajihollahi; Benjamin M. W. Tsui; Dean F. Wong; Vesna Sossi (IEEE Trans. Medical Imaging, 2008)

Cannaboid CB1 receptor imaging in vivo in schizophrenia by positron emission tomography. - Dean F. Wong; Hiroto Kuwabara; Andrew G. Horti; Vanessa Raymont; James R. Brasic; Maria Guevara; Blanca Bisuna; Ayon Nandi; Arman Rahmim; Nicola Cascella (NeuroImage, 2010)

Quantification of cerebral cannabinoid receptors subtype 1 (CB1) in healthy subjects and schizophrenia by the novel PET radioligand [11C]OMAR. - Dean F. Wong; Hiroto Kuwabara; Andrew G. Horti; Vanessa Raymont; James R. Brasic; Maria Guevara; Weiguo Ye; Robert F. Dannals; Hayden T. Ravert; Ayon Nandi; Arman Rahmim; Jeffrey E. Ming; et al. (NeuroImage, 2010)

X-ray CT Metal Artifact Reduction Using Wavelet Domain $L_{0}$ Sparse Regularization. - Abolfazl Mehranian; Mohammad Reza Ay; Arman Rahmim; Habib Zaidi (IEEE Trans. Medical Imaging, 2013)

Anatomy-guided brain PET imaging incorporating a joint prior model. - Lijun Lu; Jianhua Ma 001; Jing Tang 005; Qianjin Feng; Arman Rahmim; Wufan Chen (ISBI, 2014)

Ultrasound Tomosynthesis: A New Paradigm for Quantitative Imaging of the Prostate. - Fereshteh Aalamifar; Reza Seifabadi; Marcelino Bernardo; Ayele H. Negussie; Baris Turkbey; María Merino 002; Peter A. Pinto; Arman Rahmim; Bradford J. Wood; Emad M. Boctor (MICCAI (1), 2016)

Blood flow and endothelial cell phenotype regulation during sprouting angiogenesis. - Hossein Bazmara; Madjid Soltani; Mostafa Sefidgar; Majid Bazargan; Mojtaba Mousavi Naeenian; Arman Rahmim (Medical Biol. Eng. Comput., 2016)

A radiative transfer equation-based image-reconstruction method incorporating boundary conditions for diffuse optical imaging. - Abhinav K. Jha; Yansong Zhu; Dean F. Wong; Arman Rahmim (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2017)

Linking dopaminergic reward signals to the development of attentional bias: A positron emission tomographic study. - Brian A. Anderson; Hiroto Kuwabara; Dean F. Wong; Joshua Roberts; Arman Rahmim; James R. Brasic; Susan M. Courtney (NeuroImage, 2017)

Radiomics analysis of baseline F-FDG PET/CT images for improved prognosis in nasopharyngeal carcinoma. - Wenbing Lv; Qingyu Yuan; Quanshi Wang; Jianhua Ma 001; Qianjin Feng; Wufan Chen; Arman Rahmim; Lijun Lu (ISBI, 2018)

Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition. - Lijun Lu; Xiaomian Ma; Hassan Mohy-ud-Din; Jianhua Ma 001; Qianjin Feng; Arman Rahmim; Wufan Chen (Comput. Methods Programs Biomed., 2018)

An Analysis Scheme for Investigation of Effects of Various Parameters on Signals in Acoustic-Resolution Photoacoustic Microscopy of Mice Brain: a Simulation Study. - Hossein Ghadiri; Mohammad Reza Fouladi; Arman Rahmim (CoRR, 2018)

Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease. - Mohammad R. Salmanpour; Mojtaba Shamsaei; Abdollah Saberi; Saeed Setayeshi 001; Ivan S. Klyuzhin; Vesna Sossi; Arman Rahmim (Comput. Biol. Medicine, 2019)

PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients. - Isaac Shiri; Hassan Maleki; Ghasem Hajianfar; Hamid Abdollahi; Saeed Ashrafinia; Mathieu Hatt; Mehrdad Oveisi; Arman Rahmim (CoRR, 2019)

Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches. - Isaac Shiri; Hassan Maleki; Ghasem Hajianfar; Hamid Abdollahi; Saeed Ashrafinia; Mathieu Hatt; Mehrdad Oveisi; Arman Rahmim (CoRR, 2019)

Imager-4D: New Software for Viewing Dynamic PET Scans and Extracting Radiomic Parameters from PET Data. - Steven P. Rowe; Lilja B. Solnes; Yafu Yin; Grant B. Kitchen; Martin A. Lodge; Nicolas A. Karakatsanis; Arman Rahmim; Martin G. Pomper; Jeffrey P. Leal (J. Digit. Imaging, 2019)

GAN-Based Bi-Modal Segmentation Using Mumford-Shah Loss: Application to Head and Neck Tumors in PET-CT Images. - Fereshteh Yousefirizi; Arman Rahmim (HECKTOR@MICCAI, 2020)

Multi-Level Multi-Modality Fusion Radiomics: Application to PET and CT Imaging for Prognostication of Head and Neck Cancer. - Wenbing Lv; Saeed Ashrafinia; Jianhua Ma 001; Lijun Lu; Arman Rahmim (IEEE J. Biomed. Health Informatics, 2020)

Advanced Automatic Segmentation of Tumors and Survival Prediction in Head and Neck Cancer. - Mohammad R. Salmanpour; Ghasem Hajianfar; Seyed Masoud Rezaeijo; Mohammad Mahdi Ghaemi; Arman Rahmim (HECKTOR@MICCAI, 2021)

Segmentation and Risk Score Prediction of Head and Neck Cancers in PET/CT Volumes with 3D U-Net and Cox Proportional Hazard Neural Networks. - Fereshteh Yousefirizi; Ian Janzen; Natalia Dubljevic; Yueh-En Liu; Chloe Hill; Calum MacAulay; Arman Rahmim (HECKTOR@MICCAI, 2021)

Improved motor outcome prediction in Parkinson's disease applying deep learning to DaTscan SPECT images. - Matthew P. Adams; Arman Rahmim; Jing Tang 005 (Comput. Biol. Medicine, 2021)

Artificial intelligence-driven assessment of radiological images for COVID-19. - Yassine Bouchareb; Pegah Moradi Khaniabadi; Faiza Al Kindi; Humoud Al Dhuhli; Isaac Shiri; Habib Zaidi; Arman Rahmim (Comput. Biol. Medicine, 2021)

Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning. - Mohammad R. Salmanpour; Mojtaba Shamsaei; Abdollah Saberi; Ghasem Hajianfar; Hamid Soltanian-Zadeh; Arman Rahmim (Comput. Biol. Medicine, 2021)

Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients. - Isaac Shiri; Majid Sorouri; Parham Geramifar; Mostafa Nazari; Mohammad Abdollahi; Yazdan Salimi; Bardia Khosravi; Dariush Askari; Leila Aghaghazvini; Ghasem Hajianfar; Amir Kasaeian; Hamid Abdollahi; et al. (Comput. Biol. Medicine, 2021)

Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease. - Mohammad R. Salmanpour; Mojtaba Shamsaei; Arman Rahmim (Comput. Methods Programs Biomed., 2021)

Artificial Intelligence in PET: an Industry Perspective. - Arkadiusz Sitek; Sangtae Ahn; Evren Asma; Adam Chandler; Alvin Ihsani; Sven Prevrhal; Arman Rahmim; Babak Saboury; Kris Thielemans (CoRR, 2021)

A brief history of AI: how to prevent another winter (a critical review). - Amirhosein Toosi; Andrea Bottino; Babak Saboury; Eliot L. Siegel; Arman Rahmim (CoRR, 2021)

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics. - Fereshteh Yousefirizi; Pierre Decazes; Amine Amyar; Su Ruan; Babak Saboury; Arman Rahmim (CoRR, 2021)

3-D PET Image Generation with tumour masks using TGAN. - Robert V. Bergen; Jean-François Rajotte; Fereshteh Yousefirizi; Ivan S. Klyuzhin; Arman Rahmim; Raymond T. Ng (CoRR, 2021)

Advanced survival prediction in head and neck cancer using hybrid machine learning systems and radiomics features. - Mohammad R. Salmanpour; Mahdi Hosseinzadeh; Ensiyeh Modiri; Azizeh Akbari; Ghasem Hajianfar; Dariush Askari; Mehdi Fatan; Mehdi Maghsudi; Hanieh Ghaffari; Seyed Masoud Rezaeijo; Mohammad Mahdi Ghaemi; Arman Rahmim (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2022)

Prediction of TNM stage in head and neck cancer using hybrid machine learning systems and radiomics features. - Mohammad R. Salmanpour; Mahdi Hosseinzadeh; Azizeh Akbari; Kasra Borazjani; Kasra Mojallal; Dariush Askari; Ghasem Hajianfar; Seyed Masoud Rezaeijo; Mohammad Mahdi Ghaemi; Amir Hossein Nabizadeh; Arman Rahmim (Computer-Aided Diagnosis, 2022)

A U-Net Convolutional Neural Network with Multiclass Dice Loss for Automated Segmentation of Tumors and Lymph Nodes from Head and Neck Cancer PET/CT Images. - Shadab Ahamed; Luke Polson; Arman Rahmim (HECKTOR@MICCAI, 2022)

Deep Learning and Machine Learning Techniques for Automated PET/CT Segmentation and Survival Prediction in Head and Neck Cancer. - Mohammad R. Salmanpour; Ghasem Hajianfar; Mahdi Hosseinzadeh; Seyed Masoud Rezaeijo; Mohammad Mehdi Hosseini; Ehsanhosein Kalatehjari; Ali Harimi; Arman Rahmim (HECKTOR@MICCAI, 2022)

A cascaded deep network for automated tumor detection and segmentation in clinical PET imaging of diffuse large B-cell lymphoma. - Shadab Ahamed; Natalia Dubljevic; Ingrid Bloise; Claire Gowdy; Patrick Martineau; Don Wilson; Carlos F. Uribe; Arman Rahmim; Fereshteh Yousefirizi (Image Processing, 2022)

3D PET image generation with tumour masks using TGAN. - Robert V. Bergen; Jean-François Rajotte; Fereshteh Yousefirizi; Ivan S. Klyuzhin; Arman Rahmim; Raymond T. Ng (Image Processing, 2022)

Multi-modality fusion coupled with deep learning for improved outcome prediction in head and neck cancer. - Arash Javanmardi; Mahdi Hosseinzadeh; Ghasem Hajianfar; Amir Hossein Nabizadeh; Seyed Masoud Rezaeijo; Arman Rahmim; Mohammad R. Salmanpour (Image Processing, 2022)

Convolutional neural network with a hybrid loss function for fully automated segmentation of lymphoma lesions in FDG PET images. - Fereshteh Yousefirizi; Natalia Dubljevic; Shadab Ahamed; Ingrid Bloise; Claire Gowdy; Joo Hyun O; Youssef Farag; Rodrigue de Schaetzen; Patrick Martineau; Don Wilson; Carlos F. Uribe; Arman Rahmim (Image Processing, 2022)

Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics. - Pegah Moradi Khaniabadi; Yassine Bouchareb; Humoud Al Dhuhli; Isaac Shiri; Faiza Al Kindi; Bita Moradi Khaniabadi; Habib Zaidi; Arman Rahmim (Comput. Biol. Medicine, 2022)

Modeling the efficacy of different anti-angiogenic drugs on treatment of solid tumors using 3D computational modeling and machine learning. - Milad Mousavi; Mahsa Dehghan Manshadi; Madjid Soltani; Farshad Moradi Kashkooli; Arman Rahmim; Amir Mosavi; Michal Kvasnica; Peter M. Atkinson; Levente Kovács; Andras Koltay; Norbert Kiss; Hojjat Adeli (Comput. Biol. Medicine, 2022)

Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images. - Isaac Shiri; Mehdi Amini; Mostafa Nazari; Ghasem Hajianfar; Atlas Haddadi Avval; Hamid Abdollahi; Mehrdad Oveisi; Hossein Arabi; Arman Rahmim; Habib Zaidi (Comput. Biol. Medicine, 2022)

COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14, 339 patients. - Isaac Shiri; Yazdan Salimi; Masoumeh Pakbin; Ghasem Hajianfar; Atlas Haddadi Avval; Amirhossein Sanaat; Shayan Mostafaei; Azadeh Akhavanallaf; Abdollah Saberi; Zahra Mansouri; Dariush Askari; Mohammadreza Ghasemian; et al. (Comput. Biol. Medicine, 2022)

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features. - Ivan S. Klyuzhin; Yixi Xu; Anthony Ortiz; Juan Lavista Ferres; Ghassan Hamarneh; Arman Rahmim (Comput. Methods Programs Biomed., 2022)

Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features. - Arman Rahmim; Amirhosein Toosi; Mohammad R. Salmanpour; Natalia Dubljevic; Ian Janzen; Isaac Shiri; Mohamad A. Ramezani; Ren Yuan; Cheryl Ho; Habib Zaidi; Calum MacAulay; Carlos F. Uribe; et al. (CoRR, 2022)

Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine - The Bethesda Report (AI Summit 2022). - Arman Rahmim; Tyler J. Bradshaw; Irène Buvat; Joyita Dutta; Abhinav K. Jha; Paul E. Kinahan; Quanzheng Li; Chi Liu; Melissa D. McCradden; Babak Saboury; Eliot L. Siegel; John J. Sunderland; et al. (CoRR, 2022)

Head and neck tumor segmentation in PET/CT: The HECKTOR challenge. - Valentin Oreiller; Vincent Andrearczyk; Mario Jreige; Sarah Boughdad; Hesham Elhalawani; Joël Castelli; Martin Vallières; Simeng Zhu; Juanying Xie; Ying Peng; Andrei Iantsen; Mathieu Hatt; et al. (Medical Image Anal., 2022)

A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset. - Shadab Ahamed; Yixi Xu; Ingrid Bloise; Joo Hyun O; Carlos F. Uribe; Rahul Dodhia; Juan Lavista Ferres; Arman Rahmim (Image Processing, 2023)

State-of-the-art object detection algorithms for small lesion detection in PSMA PET: use of rotational maximum intensity projection (MIP) images. - Amirhosein Toosi; Sara Harsini; Shadab Ahamed; Fereshteh Yousefirizi; François Bénard; Carlos F. Uribe; Arman Rahmim (Image Processing, 2023)

Revisiting the supervision level in semi-supervised learning for automated tumor segmentation: application to lymphoma FDG PET imaging. - Fereshteh Yousefirizi; Joo Hyun O; Ingrid Bloise; Amirhosein Toosi; Carlos F. Uribe; Arman Rahmim (Image Processing, 2023)

Observer study-based evaluation of TGAN architecture used to generate oncological PET images. - Roberto Fedrigo; Fereshteh Yousefirizi; Ziping Liu; Abhinav K. Jha; Robert V. Bergen; Jean-François Rajotte; Raymond T. Ng; Ingrid Bloise; Sara Harsini; Dan J. Kadrmas; Carlos F. Uribe; Arman Rahmim (Image Perception, Observer Performance, and Technology Assessment, 2023)

Generative Adversarial Networks for Anomaly Detection in Biomedical Imaging: A Study on Seven Medical Image Datasets. - Marzieh Esmaeili; Amirhosein Toosi; Arash Roshanpoor; Vahid Changizi; Marjan Ghazisaeedi; Arman Rahmim; Mohammad Sabokrou (IEEE Access, 2023)

Generalized Dice Focal Loss trained 3D Residual UNet for Automated Lesion Segmentation in Whole-Body FDG PET/CT Images. - Shadab Ahamed; Arman Rahmim (CoRR, 2023)

Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images. - Shadab Ahamed; Yixi Xu; Claire Gowdy; Joo Hyun O; Ingrid Bloise; Don Wilson; Patrick Martineau; François Bénard; Fereshteh Yousefirizi; Rahul Dodhia; Juan M. Lavista Ferres; William B. Weeks; et al. (CoRR, 2023)

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss. - Yixi Xu; Ivan S. Klyuzhin; Sara Harsini; Anthony Ortiz; Shun Zhang; François Bénard; Rahul Dodhia; Carlos F. Uribe; Arman Rahmim; Juan Lavista Ferres (Comput. Biol. Medicine, 2023)

Prediction of drug amount in Parkinson's disease using hybrid machine learning systems and radiomics features. - Mohammad R. Salmanpour; Mahdi Hosseinzadeh; Mahya Bakhtiyari; Mehdi Maghsudi; Arman Rahmim (Int. J. Imaging Syst. Technol., 2023)

Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer. - Mohammad R. Salmanpour; Mahdi Hosseinzadeh; Seyed Masoud Rezaeijo; Arman Rahmim (Comput. Methods Programs Biomed., 2023)

Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging. - Niloufar Zakariaei; Arman Rahmim; Eldad Haber (CMMCA@MICCAI, 2024)

Thyroidiomics: An Automated Pipeline for Segmentation and Classification of Thyroid Pathologies from Scintigraphy Images. - Maziar Sabouri; Shadab Ahamed; Azin Asadzadeh; Atlas Haddadi Avval; Soroush Bagheri; Mohsen Arabi; Seyed Rasoul Zakavi; Emran Askari; Ali Rasouli; Atena Aghaee; Mohaddese Sehati; Fereshteh Yousefirizi; et al. (EUVIP, 2024)

How to Segment in 3D Using 2D Models: Automated 3D Segmentation of Prostate Cancer Metastatic Lesions on PET Volumes Using Multi-angle Maximum Intensity Projections and Diffusion Models. - Amirhosein Toosi; Sara Harsini; François Bénard; Carlos F. Uribe; Arman Rahmim (DGM4MICCAI@MICCAI, 2024)

Spatiotemporal modeling of radiopharmaceutical transport in solid tumors: Application to 177Lu-PSMA therapy of prostate cancer. - Anahita Piranfar; Madjid Soltani; Farshad Moradi Kashkooli; Carlos F. Uribe; Arman Rahmim (Comput. Methods Programs Biomed., 2024)

A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset. - Shadab Ahamed; Yixi Xu; Ingrid Bloise; Joo H. O; Carlos F. Uribe; Rahul Dodhia; Juan Lavista Ferres; Arman Rahmim (CoRR, 2024)

MEDDAP: Medical Dataset Enhancement via Diversified Augmentation Pipeline. - Yasamin Medghalchi; Niloufar Zakariaei; Arman Rahmim; Ilker Hacihaliloglu (CoRR, 2024)

IgCONDA-PET: Implicitly-Guided Counterfactual Diffusion for Detecting Anomalies in PET Images. - Shadab Ahamed; Yixi Xu; Arman Rahmim (CoRR, 2024)

Segmentation-Free Outcome Prediction in Head and Neck Cancer: Deep Learning-based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs) of PET Images. - Amirhosein Toosi; Isaac Shiri; Habib Zaidi; Arman Rahmim (CoRR, 2024)

Nuclear Medicine Artificial Intelligence in Action: The Bethesda Report (AI Summit 2024). - Arman Rahmim; Tyler J. Bradshaw; Guido Davidzon; Joyita Dutta; Georges El Fakhri; Munir Ghesani; Nicolas A. Karakatsanis; Quanzheng Li; Chi Liu; Emilie Roncali; Babak Saboury; Tahir Yusufaly; et al. (CoRR, 2024)

Deep Optimal Experimental Design for Parameter Estimation Problems. - Md Shahriar Rahim Siddiqui; Arman Rahmim; Eldad Haber (CoRR, 2024)

Prognosis of COVID-19 using Artificial Intelligence: A Systematic Review and Meta-analysis. - SaeedReza Motamedian; Sadra Mohaghegh; Elham Babadi Oregani; Mahrsa Amjadi; Parnian Shobeiri; Negin Cheraghi; Niusha Solouki; Nikoo Ahmadi; Mohammad-Rahimi Hossein; Yassine Bouchareb; Arman Rahmim (CoRR, 2024)

Machine Learning Evaluation Metric Discrepancies across Programming Languages and Their Components: Need for Standardization. - Mohammad R. Salmanpour; Morteza Alizadeh; Ghazal Mousavi; Saba Sadeghi; Sajad Amiri; Mehrdad Oveisi; Arman Rahmim; Ilker Hacihaliloglu (CoRR, 2024)

Enhanced Lung Cancer Survival Prediction using Semi-Supervised Pseudo-Labeling and Learning from Diverse PET/CT Datasets. - Mohammad R. Salmanpour; Arman Gorji; Amin Mousavi; Ali Fathi Jouzdani; Nima Sanati; Mehdi Maghsudi; Bonnie Leung; Cheryl Ho; Ren Yuan; Arman Rahmim (CoRR, 2024)

Biological and Radiological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0. - Mohammad R. Salmanpour; Sajad Amiri; Sara Gharibi; Ahmad Shariftabrizi; Yixi Xu; William B. Weeks; Arman Rahmim; Ilker Hacihaliloglu (CoRR, 2024)

Assessing privacy leakage in synthetic 3-D PET imaging using transversal GAN. - Robert V. Bergen; Jean-François Rajotte; Fereshteh Yousefirizi; Arman Rahmim; Raymond T. Ng (Comput. Methods Programs Biomed., 2024)

Differentiation of COVID-19 pneumonia from other lung diseases using CT radiomic features and machine learning: A large multicentric cohort study. - Isaac Shiri; Yazdan Salimi; Abdollah Saberi; Masoumeh Pakbin; Ghasem Hajianfar; Atlas Haddadi Avval; Amirhossein Sanaat; Azadeh Akhavanallaf; Shayan Mostafaei; Zahra Mansouri; Dariush Askari; Mohammadreza Ghasemian; et al. (Int. J. Imaging Syst. Technol., 2024)

SlicerSPECTRecon: A 3D Slicer Extension for SPECT Image Reconstruction. - Obed Dzikunu; Maziar Sabouri; Shadab Ahamed; Carlos F. Uribe; Arman Rahmim; Lucas A. Polson (J. Open Source Softw., 2024)

Machine Learning Evaluation Metric Discrepancies Across Programming Languages and Their Components in Medical Imaging Domains: Need for Standardization. - Mohammad R. Salmanpour; Morteza Alizadeh; Ghazal Mousavi; Saba Sadeghi; Sajad Amiri; Mehrdad Oveisi; Arman Rahmim; Ilker Hacihaliloglu (IEEE Access, 2025)

IgCONDA-PET: Weakly-supervised PET anomaly detection using implicitly-guided attention-conditional counterfactual diffusion modeling - a multi-center, multi-cancer, and multi-tracer study. - Shadab Ahamed; Arman Rahmim (Comput. Medical Imaging Graph., 2025)

PyTomography: A python library for medical image reconstruction. - Lucas A. Polson; Roberto Fedrigo; Chenguang Li; Maziar Sabouri; Obed Dzikunu; Shadab Ahamed; Nicolas A. Karakatsanis; Sara Kurkowska; Peyman Sheikhzadeh; Pedro L. Esquinas; Arman Rahmim; Carlos F. Uribe (SoftwareX, 2025)

Adaptive Voxel-Weighted Loss Using L1 Norms in Deep Neural Networks for Detection and Segmentation of Prostate Cancer Lesions in PET/CT Images. - Obed Korshie Dzikunu; Shadab Ahamed; Amirhossein Toosi; Xiaoxiao Li; Arman Rahmim (CoRR, 2025)

AI-Augmented Thyroid Scintigraphy for Robust Classification. - Maziar Sabouri; Ghasem Hajianfar; Alireza Rafiei Sardouei; Milad Yazdani; Azin Asadzadeh; Soroush Bagheri; Mohsen Arabi; Seyed Rasoul Zakavi; Emran Askari; Atena Aghaee; Dena Shahriari; Habib Zaidi; et al. (CoRR, 2025)

Comprehensive Evaluation of Quantitative Measurements from Automated Deep Segmentations of PSMA PET/CT Images. - Obed Korshie Dzikunu; Amirhossein Toosi; Shadab Ahamed; Sara Harsini; François Bénard; Xiaoxiao Li; Arman Rahmim (CoRR, 2025)

Pathobiological Dictionary Defining Pathomics and Texture Features: Addressing Understandable AI Issues in Personalized Liver Cancer; Dictionary Version LCP1.0. - Mohammad R. Salmanpour; Seyed Mohammad Piri; Somayeh Sadat Mehrnia; Ahmad Shariftabrizi; Masume Allahmoradi; Venkata SK. Manem; Arman Rahmim; Ilker Hacihaliloglu (CoRR, 2025)

AllMetrics: A Unified Python Library for Standardized Metric Evaluation and Robust Data Validation in Machine Learning. - Morteza Alizadeh; Mehrdad Oveisi; Sonya Falahati; Ghazal Mousavi; Mohsen Alambardar Meybodi; Somayeh Sadat Mehrnia; Ilker Hacihaliloglu; Arman Rahmim; Mohammad R. Salmanpour (CoRR, 2025)

RT-utils: A Minimal Python Library for RT-struct Manipulation. - Asim Shrestha; Adam Watkins; Fereshteh Yousefirizi; Arman Rahmim; Carlos F. Uribe (J. Open Source Softw., 2025)

Emerging Frameworks for Objective Task-based Evaluation of Quantitative Medical Imaging Methods. - Yan Liu; Huitian Xia; Nancy A. Obuchowski; Richard Laforest; Arman Rahmim; Barry A. Siegel; Abhinav K. Jha (CoRR, 2025)

Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation. - Mohammad R. Salmanpour; Amir Hossein Pouria; Sonia Falahati; Shahram Taeb; Somayeh Sadat Mehrnia; Mehdi Maghsudi; Ali Fathi Jouzdani; Mehrdad Oveisi; Ilker Hacihaliloglu; Arman Rahmim (CoRR, 2025)

Radiological and Biological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Breast Cancer; Dictionary Version BM1.0. - Arman Gorji; Nima Sanati; Amir Hossein Pouria; Somayeh Sadat Mehrnia; Ilker Hacihaliloglu; Arman Rahmim; Mohammad R. Salmanpour (CoRR, 2025)

Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging. - Mohammad R. Salmanpour; Somayeh Sadat Mehrnia; Sajad Jabarzadeh Ghandilu; Zhino Safahi; Sonya Falahati; Shahram Taeb; Ghazal Mousavi; Mehdi Maghsoudi; Ahmad Shariftabrizi; Ilker Hacihaliloglu; Arman Rahmim (CoRR, 2025)

Uncertainty Propagation From Projections to Region Counts in Tomographic Imaging: Application to Radiopharmaceutical Dosimetry. - Lucas A. Polson; Sara Kurkowska; Chenguang Li; Pedro L. Esquinas; Peyman Sheikhzadeh; Mehrshad Abbasi; François Bénard; Carlos F. Uribe; Arman Rahmim (IEEE Trans. Medical Imaging, 2025)

Enhancing radiomics robustness using bayesian penalized likelihood PET reconstruction: application to Phantom and non-small cell lung cancer patient studies. - Zahra Valibeiglou; Jalil Pirayesh Islamian; Yunus Soleymani; Saeed Farzanehfar; Farahnaz Aghahosseini; Neda Gilani; Arman Rahmim; Peyman Sheikhzadeh (BMC Medical Imaging, 2025)