Mana Moassefi

According to our database, Mana Moassefi authored at least 15 papers between 2021 and 2025.

Collaborative distances:

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

2025

Correction: Checklist for Reproducibility of Deep Learning in Medical Imaging.

Mana Moassefi, Yashbir Singh, Gian Marco Conte, Bardia Khosravi, Pouria Rouzrokh, Sanaz Vahdati, Nabile M. Safdar, Linda Moy, Felipe Kitamura, Amilcare Gentili, Paras Lakhani, Nina Kottler, Safwan S. Halabi, Joseph H. Yacoub, Yuankai Hou, Khaled Younis, Bradley J. Erickson, Elizabeth A. Krupinski, Shahriar Faghani

J. Imaging Inform. Medicine, 2025

Cross-Institutional Evaluation of Large Language Models for Radiology Diagnosis Extraction: A Prompt-Engineering Perspective.

Mana Moassefi, Sina Houshmand, Shahriar Faghani, Peter Chang, Shawn H. Sun, Bardia Khosravi, Aakash G. Triphati, Ghulam Rasool, Neil K. Bhatia, Les R. Folio, Katherine P. Andriole, Judy W. Gichoya, Bradley J. Erickson

J. Imaging Inform. Medicine, 2025

Empowering Women in Imaging Informatics: Confronting Imposter Syndrome, Addressing Microaggressions, and Striving for Work-Life Harmony.

Mana Moassefi, Nikki Fennell, Mindy Yang, Jennifer B. Gunter, Teri M. Sippel Schmit, Tessa S. Cook

J. Imaging Inform. Medicine, 2025

My Experience with Academy - Advancing Innovation in Imaging.

Mana Moassefi

J. Imaging Inform. Medicine, 2025

RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models.

Farhad Maleki, Linda Moy, Reza Forghani, Tapotosh Ghosh, Katie L. Ovens, Steve Langer, Pouria Rouzrokh, Bardia Khosravi, Ali Ganjizadeh, Daniel I. Warren, Roxana Daneshjou, Mana Moassefi, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline

J. Imaging Inform. Medicine, 2025

Predicting IDH Mutation in Glioma Patients Using Deep Learning Algorithms with Conformal Prediction.

Danial Elyassirad, Benyamin Gheiji, Mahsa Vatanparast, Amir Mahmoud Ahmadzadeh, Mohammad Masoudi, Mobin Gholami, Mana Moassefi, Shahriar Faghani

J. Imaging Inform. Medicine, 2025

2024

A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey.

Sanaz Vahdati, Bardia Khosravi, Elham Mahmoudi, Kuan Zhang, Pouria Rouzrokh, Shahriar Faghani, Mana Moassefi, Aylin Tahmasebi, Katherine P. Andriole, Peter Chang, Keyvan Farahani, Mona G. Flores, Les R. Folio, Sina Houshmand, Maryellen L. Giger, Judy W. Gichoya, Bradley J. Erickson

J. Imaging Inform. Medicine, 2024

Checklist for Reproducibility of Deep Learning in Medical Imaging.

Mana Moassefi, Yashbir Singh, Gian Marco Conte, Bardia Khosravi, Pouria Rouzrokh, Sanaz Vahdati, Nabile M. Safdar, Linda Moy, Felipe Kitamura, Amilcare Gentili, Paras Lakhani, Nina Kottler, Safwan S. Halabi, Joseph H. Yacoub, Yuankai Hou, Khaled Younis, Bradley J. Erickson, Elizabeth A. Krupinski, Shahriar Faghani

J. Imaging Inform. Medicine, 2024

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation.

Dominic LaBella, Katherine Schumacher, Michael Mix, Kevin Leu, Shan McBurney-Lin, Pierre Nedelec, Javier E. Villanueva-Meyer, Jonathan Shapey, Tom Vercauteren, Kazumi Chia, Omar Al-Salihi, Justin Leu, Lia Halasz, Yury Velichko, Chunhao Wang, John Kirkpatrick, Scott Floyd, Zachary J. Reitman, Trey Mullikin, Ulas Bagci, Sean Sachdev, Jona A. Hattangadi-Gluth, Tyler M. Seibert, Nikdokht Farid, Connor Puett, Matthew W. Pease, Kevin Shiue, Syed Muhammad Anwar, Shahriar Faghani, Muhammad Ammar Haider, Pranav I. Warman, Jake Albrecht, András Jakab, Mana Moassefi, Verena Chung, Alejandro Aristizabal, Alexandros Karargyris, Hasan Kassem, Sarthak Pati, Micah J. Sheller, Christina Huang, Aaron Coley, Siddharth Ghanta, Alex Schneider, Conrad Sharp, Rachit Saluja, Florian Kofler, Philipp Lohmann, Philipp Vollmuth, Louis Gagnon, Maruf Adewole, Hongwei Bran Li, Anahita Fathi Kazerooni, Nourel Hoda Tahon, Udunna Anazodo, Ahmed W. Moawad, Bjoern H. Menze, Marius George Linguraru, Mariam Aboian, Benedikt Wiestler, Ujjwal Baid, Gian Marco Conte, Andreas M. Rauschecker, Ayman Nada, Aly H. Abayazeed, Raymond Y. Huang, Maria Correia de Verdier, Jeffrey D. Rudie, Spyridon Bakas, Evan Calabrese

CoRR, 2024

BraTS-Path Challenge: Assessing Heterogeneous Histopathologic Brain Tumor Sub-regions.

Spyridon Bakas, Siddhesh P. Thakur, Shahriar Faghani, Mana Moassefi, Ujjwal Baid, Verena Chung, Sarthak Pati, Shubham Innani, Bhakti Baheti, Jake Albrecht, Alexandros Karargyris, Hasan Kassem, MacLean P. Nasrallah, Jared T. Ahrendsen, Valeria Barresi, Maria A. Gubbiotti, Giselle Y. López, Calixto-Hope G. Lucas, Michael L. Miller, Lee A. D. Cooper, Jason T. Huse, William R. Bell

CoRR, 2024

Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge.

Dominic LaBella, Ujjwal Baid, Omaditya Khanna, Shan McBurney-Lin, Ryan McLean, Pierre Nedelec, Arif Rashid, Nourel Hoda Tahon, Talissa Altes, Radhika Bhalerao, Yaseen Dhemesh, Devon Godfrey, Fathi Hilal, Scott Floyd, Anastasia Janas, Anahita Fathi Kazerooni, John Kirkpatrick, Collin Kent, Florian Kofler, Kevin Leu, Nazanin Maleki, Bjoern H. Menze, Maxence Pajot, Zachary J. Reitman, Jeffrey D. Rudie, Rachit Saluja, Yury Velichko, Chunhao Wang, Pranav Warman, Maruf Adewole, Jake Albrecht, Udunna Anazodo, Syed Muhammad Anwar, Timothy Bergquist, Sully F. Chen, Verena Chung, Gian Marco Conte, Farouk Dako, James A. Eddy, Ivan Ezhov, Nastaran Khalili, Juan Eugenio Iglesias, Zhifan Jiang, Elaine Johanson, Koen Van Leemput, Hongwei Bran Li, Marius George Linguraru, Xinyang Liu, Aria Mahtabfar, Zeke Meier, Ahmed W. Moawad, John Mongan, Marie Piraud, Russell Takeshi Shinohara, Walter F. Wiggins, Aly H. Abayazeed, Rachel Akinola, András Jakab, Michel Bilello, Maria Correia de Verdier, Priscila Crivellaro, Christos Davatzikos, Keyvan Farahani, John B. Freymann, Christopher Hess, Raymond Y. Huang, Philipp Lohmann, Mana Moassefi, Matthew W. Pease, Philipp Vollmuth, Nico Sollmann, David Diffley, Khanak K. Nandolia, Daniel I. Warren, Ali Hussain, Pascal Fehringer, Yulia Bronstein, Lisa Deptula, Evan G. Stein, Mahsa Taherzadeh, Eduardo Portela de Oliveira, Aoife Haughey, Marinos Kontzialis, Luca Saba, Benjamin Turner, Melanie M. T. Brüßeler, Shehbaz Ansari, Athanasios Gkampenis, David Maximilian Weiss, Aya Mansour, Islam H. Shawali, Nikolay Yordanov, Joel M. Stein, Roula Hourani, Mohammed Yahya Moshebah, Ahmed Magdy Abouelatta, Tanvir Rizvi, Klara Willms, Dann C. Martin, Abdullah Okar

CoRR, 2024

2023

A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI.

Shahriar Faghani, Bardia Khosravi, Mana Moassefi, Gian Marco Conte, Bradley J. Erickson

J. Digit. Imaging, June, 2023

Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review.

Mana Moassefi, Pouria Rouzrokh, Gian Marco Conte, Sanaz Vahdati, Tianyuan Fu, Aylin Tahmasebi, Mira Younis, Keyvan Farahani, Amilcare Gentili, Timothy Kline, Felipe C. Kitamura, Yuankai Huo, Shiba Kuanar, Khaled Younis, Bradley J. Erickson, Shahriar Faghani

J. Imaging Inform. Medicine, 2023

2022

Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report.

Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Mana Moassefi, Sanaz Vahdati, Bradley J. Erickson

CoRR, 2022

2021

MRI Brain Tumor Segmentation Using Deep Encoder-Decoder Convolutional Neural Networks.

Benjamin B. Yan, Yujia Wei, Jaidip Manikrao M. Jagtap, Mana Moassefi, Diana V. Vera Garcia, Yashbir Singh, Sanaz Vahdati, Shahriar Faghani, Bradley J. Erickson, Gian Marco Conte

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021