Mohammad R. Salmanpour

According to our database, Mohammad R. Salmanpour authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

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., October, 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., July, 2023

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, Fereshteh Yousefirizi

CoRR, 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

Proceedings of the Medical Imaging 2022: Image Processing, 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

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022

Fusion-Based Automated Segmentation in Head and Neck Cancer via Advance Deep Learning Techniques.

Seyed Masoud Rezaeijo, Ali Harimi, Mohammad R. Salmanpour

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 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 M. Ghaemi, Amir Hossein Nabizadeh, Arman Rahmim

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

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 M. Ghaemi, Arman Rahmim

Proceedings of the Medical Imaging 2022: Biomedical Applications in Molecular, 2022

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

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

Advanced Automatic Segmentation of Tumors and Survival Prediction in Head and Neck Cancer.

Mohammad R. Salmanpour, Ghasem Hajianfar, Seyed Masoud Rezaeijo, Mohammad Ghaemi, Arman Rahmim

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

Fusion-Based Head and Neck Tumor Segmentation and Survival Prediction Using Robust Deep Learning Techniques and Advanced Hybrid Machine Learning Systems.

Mehdi Fatan, Mahdi Hosseinzadeh, Dariush Askari, Hossein Sheikhi, Seyed Masoud Rezaeijo, Mohammad R. Salmanpour

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

2019

Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease.

Mohammad R. Salmanpour, Mojtaba Shamsaei, Abdollah Saberi, Saeed Setayeshi, Ivan S. Klyuzhin, Vesna Sossi, Arman Rahmim

Comput. Biol. Medicine, 2019