Bradley J Erickson (Bardia Khosravi, B Erickson, B J Erickson)

ORCID

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 79

Top Venues

Radiology. Artificial intelligence

Radiology

AJNR. American journal of neuroradiology

Journal of imaging informatics in medicine

Mayo Clinic Minnesota

Mayo Graduate School (PHD)

This page only lists publications with an associated author ORCID identifier.

Affiliation History

Mayo Clinic Minnesota Jul 01 1994

United States

Associate Chair for Research :: Radiology

Education History

Mayo Graduate School Aug 01 1985 - May 23 1989

United States

PHD :: Physiology and Biophysics

Publications

Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology 45 (4) (2024)
Sanaz Vahdati, Bardia Khosravi, Kathryn A Robinson, Pouria Rouzrokh, Mana Moassefi, Zeynettin Akkus, Bradley J Erickson
A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging. Bioengineering (Basel, Switzerland) 11 (7) (2024)
Felipe Campos Kitamura, Luciano M Prevedello, Errol Colak, Safwan S Halabi, Matthew P Lungren, Robyn L Ball, Jayashree Kalpathy-Cramer, Charles E Kahn, Tyler Richards, Jason F Talbott, George Shih, Hui Ming Lin, Katherine P Andriole, Maryam Vazirabad, Bradley J Erickson, Adam E Flanders, John T Mongan
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges. Radiology. Artificial intelligence 6 (3) (2024)
Mana Moassefi, Bradley J Erickson
Bridging Pixels to Genes. Radiology. Artificial intelligence 6 (4) (2024)
Mana Moassefi, Bradley J Erickson
Bridging Pixels to Genes. Radiology. Artificial intelligence 6 (4) (2024)
M M Zoghby, Bradley J Erickson, Gian Marco Conte
Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. Journal of imaging informatics in medicine 37 (3) (2024)
Felipe Campos Kitamura, Luciano M Prevedello, Errol Colak, Safwan S Halabi, Matthew P Lungren, Robyn L Ball, Jayashree Kalpathy-Cramer, Charles E Kahn, Tyler Richards, Jason F Talbott, George Shih, Hui Ming Lin, Katherine P Andriole, Maryam Vazirabad, Bradley J Erickson, Adam E Flanders, John T Mongan
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges. Radiology. Artificial intelligence 6 (3) (2024)
Stephanie K Zawada, Ali Ganjizadeh, Clint E Hagen, Bart M Demaerschalk, Bradley J Erickson
Feasibility of Observing Cerebrovascular Disease Phenotypes with Smartphone Monitoring: Study Design Considerations for Real-World Studies. Sensors (Basel, Switzerland) 24 (11) (2024)
Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology 45 (4) (2024)
Mana Moassefi, Bradley J Erickson
Bridging Pixels to Genes. Radiology. Artificial intelligence 6 (4) (2024)
Stephanie K Zawada, Ali Ganjizadeh, Gian Marco Conte, Bart M Demaerschalk, Bradley J Erickson
Accelerometer-Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank. Journal of the American Heart Association 13 (11) (2024)
Shahriar Faghani, Bradley J Erickson
Bone Age Prediction under Stress. Radiology. Artificial intelligence 6 (3) (2024)
Shahriar Faghani, Bradley J Erickson
Bone Age Prediction under Stress. Radiology. Artificial intelligence 6 (3) (2024)
Jason C Cai, Hirotsugu Nakai, Shiba P Kuanar, Adam T Froemming, Candice W Bolan, Akira Kawashima, Hiroaki Takahashi, Lance A Mynderse, Chandler D Dora, Mitchell R Humphreys, Panagiotis Korffiatis, Pouria Rouzrokh, Alexander K Bratt, Gian Marco Conte, Bradley J Erickson, Naoki Takahashi
Fully Automated Deep Learning Model to Detect Clinically Significant Prostate Cancer at MRI. Radiology 312 (2) (2024)
Stephanie K Zawada, Ali Ganjizadeh, Gian Marco Conte, Bart M Demaerschalk, Bradley J Erickson
Accelerometer-Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank. Journal of the American Heart Association 13 (11) (2024)
Jason C Cai, Hirotsugu Nakai, Shiba P Kuanar, Adam T Froemming, Candice W Bolan, Akira Kawashima, Hiroaki Takahashi, Lance A Mynderse, Chandler D Dora, Mitchell R Humphreys, Panagiotis Korffiatis, Pouria Rouzrokh, Alexander K Bratt, Gian Marco Conte, Bradley J Erickson, Naoki Takahashi
Fully Automated Deep Learning Model to Detect Clinically Significant Prostate Cancer at MRI. Radiology 312 (2) (2024)
Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology 45 (4) (2024)
Jason C Cai, Hirotsugu Nakai, Shiba P Kuanar, Adam T Froemming, Candice W Bolan, Akira Kawashima, Hiroaki Takahashi, Lance A Mynderse, Chandler D Dora, Mitchell R Humphreys, Panagiotis Korffiatis, Pouria Rouzrokh, Alexander K Bratt, Gian Marco Conte, Bradley J Erickson, Naoki Takahashi
Fully Automated Deep Learning Model to Detect Clinically Significant Prostate Cancer at MRI. Radiology 312 (2) (2024)
Sanaz Vahdati, Bardia Khosravi, Kathryn A Robinson, Pouria Rouzrokh, Mana Moassefi, Zeynettin Akkus, Bradley J Erickson
A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging. Bioengineering (Basel, Switzerland) 11 (7) (2024)
Kuan Zhang, Bardia Khosravi, Sanaz Vahdati, Bradley J Erickson
FDA Review of Radiologic AI Algorithms: Process and Challenges. Radiology 310 (1) (2024)
Shahriar Faghani, Cooper Gamble, Bradley J Erickson
Uncover This Tech Term: Uncertainty Quantification for Deep Learning. Korean journal of radiology 25 (4) (2024)
Sanaz Vahdati, Bardia Khosravi, Kathryn A Robinson, Pouria Rouzrokh, Mana Moassefi, Zeynettin Akkus, Bradley J Erickson
A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging. Bioengineering (Basel, Switzerland) 11 (7) (2024)
Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology 45 (4) (2024)
Pouria Rouzrokh, Bradley J Erickson
Invited Commentary: The Double-edged Sword of Bias in Medical Imaging Artificial Intelligence. Radiographics : a review publication of the Radiological Society of North America, Inc 44 (5) (2024)
Stephanie K Zawada, Ali Ganjizadeh, Gian Marco Conte, Bart M Demaerschalk, Bradley J Erickson
Accelerometer-Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank. Journal of the American Heart Association (2024)
Shahriar Faghani, Bradley J Erickson
Bone Age Prediction under Stress. Radiology. Artificial intelligence 6 (3) (2024)
Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology 45 (4) (2024)
Pouria Rouzrokh, Bradley J Erickson
Invited Commentary: The Double-edged Sword of Bias in Medical Imaging Artificial Intelligence. Radiographics : a review publication of the Radiological Society of North America, Inc 44 (5) (2024)
M M Zoghby, Bradley J Erickson, Gian Marco Conte
Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. Journal of imaging informatics in medicine 37 (3) (2024)
Felipe Campos Kitamura, Luciano M Prevedello, Errol Colak, Safwan S Halabi, Matthew P Lungren, Robyn L Ball, Jayashree Kalpathy-Cramer, Charles E Kahn, Tyler Richards, Jason F Talbott, George Shih, Hui Ming Lin, Katherine P Andriole, Maryam Vazirabad, Bradley J Erickson, Adam E Flanders, John T Mongan
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges. Radiology. Artificial intelligence 6 (3) (2024)
Stephanie K Zawada, Ali Ganjizadeh, Clint E Hagen, Bart M Demaerschalk, Bradley J Erickson
Feasibility of Observing Cerebrovascular Disease Phenotypes with Smartphone Monitoring: Study Design Considerations for Real-World Studies. Sensors (Basel, Switzerland) 24 (11) (2024)
Felipe Campos Kitamura, Luciano M Prevedello, Errol Colak, Safwan S Halabi, Matthew P Lungren, Robyn L Ball, Jayashree Kalpathy-Cramer, Charles E Kahn, Tyler Richards, Jason F Talbott, George Shih, Hui Ming Lin, Katherine P Andriole, Maryam Vazirabad, Bradley J Erickson, Adam E Flanders, John T Mongan
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges. Radiology. Artificial intelligence (2024)
Stephanie K Zawada, Ali Ganjizadeh, Gian Marco Conte, Bart M Demaerschalk, Bradley J Erickson
Accelerometer-Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank. Journal of the American Heart Association 13 (11) (2024)
Shahriar Faghani, Cooper Gamble, Bradley J Erickson
Uncover This Tech Term: Uncertainty Quantification for Deep Learning. Korean journal of radiology 25 (4) (2024)
Kuan Zhang, Bardia Khosravi, Sanaz Vahdati, Bradley J Erickson
FDA Review of Radiologic AI Algorithms: Process and Challenges. Radiology 310 (1) (2024)
Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology (2024)
Shahriar Faghani, Mana Moassefi, Ajay A Madhavan, Ian T Mark, Jared T Verdoorn, Bradley J Erickson, John C Benson
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach. AJNR. American journal of neuroradiology 45 (4) (2024)
Shahriar Faghani, Cooper Gamble, Bradley J Erickson
Uncover This Tech Term: Uncertainty Quantification for Deep Learning. Korean journal of radiology 25 (4) (2024)
Stephanie K Zawada, Ali Ganjizadeh, Gian Marco Conte, Bart M Demaerschalk, Bradley J Erickson
Accelerometer-Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank. Journal of the American Heart Association 13 (11) (2024)
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 Folio, Sina Houshmand, Maryellen L Giger, Judy W Gichoya, Bradley J Erickson
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. Journal of imaging informatics in medicine (2024)
M M Zoghby, Bradley J Erickson, Gian Marco Conte
Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. Journal of imaging informatics in medicine 37 (3) (2024)
Shahriar Faghani, Cooper Gamble, Bradley J Erickson
Uncover This Tech Term: Uncertainty Quantification for Deep Learning. Korean journal of radiology 25 (4) (2024)
M M Zoghby, Bradley J Erickson, Gian Marco Conte
Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. Journal of imaging informatics in medicine (2024)
M M Zoghby, Bradley J Erickson, Gian Marco Conte
Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. Journal of imaging informatics in medicine 37 (3) (2024)
Mana Moassefi, Bradley J Erickson
Bridging Pixels to Genes. Radiology. Artificial intelligence 6 (4) (2024)
Shahriar Faghani, Mana Moassefi, Pouria Rouzrokh, Bardia Khosravi, Francis I Baffour, Michael D Ringler, Bradley J Erickson
Quantifying Uncertainty in Deep Learning of Radiologic Images. Radiology 308 (2) (2023)
Bardia Khosravi, John P Mickley, Pouria Rouzrokh, Michael J Taunton, A Noelle Larson, Bradley J Erickson, Cody C Wyles
Anonymizing Radiographs Using an Object Detection Deep Learning Algorithm. Radiology. Artificial intelligence 5 (6) (2023)
Shahriar Faghani, Bardia Khosravi, Mana Moassefi, Gian Marco Conte, Bradley J Erickson
A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI. Journal of digital imaging (2023)
Pouria Rouzrokh, Bardia Khosravi, Sanaz Vahdati, Mana Moassefi, Shahriar Faghani, Elham Mahmoudi, Hamid Chalian, Bradley J Erickson
Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature. Current radiology reports (2022)
Mario Hevesi, Cody C Wyles, Pouria Rouzrokh, Bradley J Erickson, Hilal Maradit-Kremers, David G Lewallen, Michael J Taunton, Robert T Trousdale, Daniel J Berry
Redefining the 3D Topography of the Acetabular Safe Zone: A Multivariable Study Evaluating Prosthetic Hip Stability. The Journal of bone and joint surgery. American volume 104 (3) (2022)
Pouria Rouzrokh, Bradley J Erickson, Quinn J Johnson, Shahriar Faghani, Diana V Vera Garcia, Bradley J Erickson, Hilal Maradit-Kremers, Michael J Taunton, Cody C Wyles
Applying Deep Learning to Establish a Total Hip Arthroplasty Radiography Registry: A Stepwise Approach. The Journal of bone and joint surgery. American volume 104 (18) (2022)
Pouria Rouzrokh, Bardia Khosravi, Sanaz Vahdati, Mana Moassefi, Shahriar Faghani, Elham Mahmoudi, Hamid Chalian, Bradley J Erickson
Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature. Current radiology reports (2022)
Pouria Rouzrokh, Cody C Wyles, Shyam J Kurian, Taghi Ramazanian, Jason C Cai, Qiao Huang, Kuan Zhang, Michael J Taunton, Hilal Maradit-Kremers, Bradley J Erickson
Deep Learning for Radiographic Measurement of Femoral Component Subsidence Following Total Hip Arthroplasty. Radiology. Artificial intelligence 4 (3) (2022)
Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Mana Moassefi, Diana V Vera Garcia, Yashbir Singh, Kuan Zhang, Gian Marco Conte, Bradley J Erickson
Mitigating Bias in Radiology Machine Learning: 1. Data Handling. Radiology. Artificial intelligence 4 (5) (2022)
Shahriar Faghani, Bardia Khosravi, Kuan Zhang, Mana Moassefi, Jaidip Manikrao Jagtap, Fred Nugen, Sanaz Vahdati, Shiba P Kuanar, Seyed Moein Rassoulinejad-Mousavi, Yashbir Singh, Diana V Vera Garcia, Pouria Rouzrokh, Bradley J Erickson
Mitigating Bias in Radiology Machine Learning: 3. Performance Metrics. Radiology. Artificial intelligence 4 (5) (2022)
Bardia Khosravi, Pouria Rouzrokh, Hilal Maradit-Kremers, Dirk R Larson, Quinn J Johnson, Shahriar Faghani, Walter K Kremers, Bradley J Erickson, Rafael J Sierra, Michael J Taunton, Cody C Wyles
Patient-specific Hip Arthroplasty Dislocation Risk Calculator: An Explainable Multimodal Machine Learning-based Approach. Radiology. Artificial intelligence 4 (6) (2022)
Bardia Khosravi, Pouria Rouzrokh, Hilal Maradit-Kremers, Dirk R Larson, Quinn J Johnson, Shahriar Faghani, Walter K Kremers, Bradley J Erickson, Rafael J Sierra, Michael J Taunton, Cody C Wyles
Patient-specific Hip Arthroplasty Dislocation Risk Calculator: An Explainable Multimodal Machine Learning-based Approach. Radiology. Artificial intelligence 4 (6) (2022)
Pouria Rouzrokh, Bardia Khosravi, Sanaz Vahdati, Mana Moassefi, Shahriar Faghani, Elham Mahmoudi, Hamid Chalian, Bradley J Erickson
Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature. Current radiology reports 11 (2) (2022)
Bardia Khosravi, Pouria Rouzrokh, Hilal Maradit-Kremers, Dirk R Larson, Quinn J Johnson, Shahriar Faghani, Walter K Kremers, Bradley J Erickson, Rafael J Sierra, Michael J Taunton, Cody C Wyles
Patient-specific Hip Arthroplasty Dislocation Risk Calculator: An Explainable Multimodal Machine Learning-based Approach. Radiology. Artificial intelligence 4 (6) (2022)
Yashbir Singh, William A Jons, John E Eaton, Mette Vesterhus, Tom Karlsen, Ida Bjoerk, Andreas Abildgaard, Kristin Kaasen Jorgensen, Trine Folseraas, Derek Little, Aliya F Gulamhusein, Kosta Petrovic, Anne Negard, Gian Marco Conte, Joseph D Sobek, Jaidip Jagtap, Sudhakar K Venkatesh, Gregory J Gores, Nicholas F LaRusso, Konstantinos N Lazaridis, Bradley J Erickson
Algebraic topology-based machine learning using MRI predicts outcomes in primary sclerosing cholangitis. European radiology experimental 6 (1) (2022)
Kuan Zhang, Bardia Khosravi, Sanaz Vahdati, Shahriar Faghani, Fred Nugen, Seyed Moein Rassoulinejad-Mousavi, Mana Moassefi, Jaidip Manikrao M Jagtap, Yashbir Singh, Pouria Rouzrokh, Bradley J Erickson
Mitigating Bias in Radiology Machine Learning: 2. Model Development. Radiology. Artificial intelligence 4 (5) (2022)
Pouria Rouzrokh, Bardia Khosravi, Sanaz Vahdati, Mana Moassefi, Shahriar Faghani, Elham Mahmoudi, Hamid Chalian, Bradley J Erickson
Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature. Current radiology reports (2022)
Bardia Khosravi, Pouria Rouzrokh, Shahriar Faghani, Mana Moassefi, Sanaz Vahdati, Elham Mahmoudi, Hamid Chalian, Bradley J Erickson
Machine Learning and Deep Learning in Cardiothoracic Imaging: A Scoping Review. Diagnostics (Basel, Switzerland) 12 (10) (2022)
Bradley J Erickson, Felipe Campos Kitamura
Magician's Corner: 9. Performance Metrics for Machine Learning Models. Radiology. Artificial intelligence 3 (3) (2021)
Gian Marco Conte, Alexander D Weston, David C Vogelsang, Kenneth A Philbrick, Jason C Cai, Maurizio Barbera, Francesco Sanvito, Daniel H Lachance, Robert B Jenkins, William Oliver Tobin, Jeanette E Eckel-Passow, Bradley J Erickson
Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model. Radiology 299 (2) (2021)
Emily B Tsai, Scott Simpson, Matthew P Lungren, Michelle Hershman, Leonid Roshkovan, Errol Colak, Bradley J Erickson, George Shih, Anouk Stein, Jayashree Kalpathy-Cramer, Jody Shen, Mona Ahmed Fouad Hafez, Susan John, Prabhakar Shantha Rajiah, Brian P Pogatchnik, John T Mongan, Emre Altinmakas, Erik R Ranschaert, Felipe Campos Kitamura, Laurens Topff, Linda Moy, Jeffrey P Kanne, Carol Chia Chia Wu
The RSNA International COVID-19 Open Radiology Database (RICORD). Radiology 299 (1) (2021)
Bradley J Erickson, Felipe Campos Kitamura
Magician's Corner: 8: How to Connect an Artificial Intelligence Tool to PACS. Radiology. Artificial intelligence 3 (1) (2021)
Bradley J Erickson, Jason C Cai
Magician's Corner: 5. Generative Adversarial Networks. Radiology. Artificial intelligence 2 (2) (2020)
Nathan Robert Huber, Andrew D Missert, Bradley J Erickson
Magician's Corner: 7. Using Convolutional Neural Networks to Reduce Noise in Medical Images. Radiology. Artificial intelligence 2 (5) (2020)
David C Vogelsang, Bradley J Erickson
Magician's Corner: 6. TensorFlow and TensorBoard. Radiology. Artificial intelligence 2 (3) (2020)
Bradley J Erickson, Jason C Cai
Magician's Corner: 4. Image Segmentation with U-Net. Radiology. Artificial intelligence 2 (1) (2020)
David F Kallmes, Bradley J Erickson
Automated Aneurysm Detection: Emerging from the Shallow End of the Deep Learning Pool. Radiology 298 (1) (2020)
Youngoh Bae, Kunaraj Kumarasamy, Issa M Ali, Panagiotis Korfiatis, Zeynettin Akkus, Bradley J Erickson
Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. Journal of digital imaging 31 (2) (2019)
Curtis P Langlotz, Bibb Allen, Bradley J Erickson, Jayashree Kalpathy-Cramer, Keith Bigelow, Tessa Sundaram Cook, Adam E Flanders, Matthew P Lungren, David S Mendelson, Jeffrey D Rudie, G E Wang, Krishna Kandarpa
A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology 291 (3) (2019)
Bradley J Erickson
Machine Learning: Discovering the Future of Medical Imaging. Journal of digital imaging 30 (4) (2019)
Bradley J Erickson
Magician's Corner: 3. Image Wrangling. Radiology. Artificial intelligence 1 (6) (2019)
Bradley J Erickson
Magician's Corner: 2. Optimizing a Simple Image Classifier. Radiology. Artificial intelligence 1 (5) (2019)
Bradley J Erickson
Magician's Corner: How to Start Learning about Deep Learning. Radiology. Artificial intelligence 1 (4) (2019)
Kathleen M Schmainda, M A Prah, S D Rand, Y Liu, Brent R Logan, Mark Muzi, Swati Rane Levendovszky, X Da, Yi Fen Yen, Jayashree Kalpathy-Cramer, Thomas L Chenevert, B Hoff, Brian D Ross, Yue Cao, Madhava Aryal, Bradley J Erickson, Panagiotis Korffiatis, Timothy Dondlinger, Laura C Bell, Leland S Hu, Paul E Kinahan, C C Quarles
Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project. AJNR. American journal of neuroradiology 39 (6) (2018)

Bradley J Erickson.css-eqlu8i{font-size:small;padding-left:4px;} (Bardia Khosravi, B Erickson, B J Erickson)

Publication Activity (10 Years)

Top Topics

Top Venues

Bradley J Erickson (Bardia Khosravi, B Erickson, B J Erickson)