Bradley J. Erickson

54 papers B 8Misc 3Journal 38Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Systematic Review on the Use of Registration-Based Change Tracking Methods in Longitudinal Radiological Images. J. Imaging Inform. Medicine Jeeho E. Im, Muhammed Khalifa, Adriana V. Gregory, Bradley J. Erickson, Timothy L. Kline
2025	J	`jnl`	A comparative analysis of privacy-preserving large language models for automated echocardiography report analysis. J. Am. Medical Informatics Assoc. Elham Mahmoudi, Sanaz Vahdati, Chieh-Ju Chao, Bardia Khosravi, Ajay Misra, Francisco Lopez-Jimenez, Bradley J. Erickson
2025	J	`jnl`	Correction: Checklist for Reproducibility of Deep Learning in Medical Imaging. J. Imaging Inform. Medicine 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
2025	J	`jnl`	EchoGraph system for automated quality assessment of echocardiography reports. npj Digit. Medicine Chieh-Ju Chao, Jean-Benoit Delbrouck, Mohammad Asadi, Imon Banerjee, Juan Maria Farina, Francesca Galasso, Ahmed K. Mahmoud, Mohammed Tiseer Abbas, Yu-Chiang Wang, Reza Arsanjani, Garvan C. Kane, Jae K. Oh, Bradley J. Erickson, Li Fei-Fei, Ehsan Adeli, Curtis Langlotz
2024	J	`jnl`	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. J. Imaging Inform. Medicine 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
2024	J	`jnl`	CONFLARE: CONFormal LArge language model REtrieval. CoRR Pouria Rouzrokh, Shahriar Faghani, Cooper U. Gamble, Moein Shariatnia, Bradley J. Erickson
2024	J	`jnl`	Checklist for Reproducibility of Deep Learning in Medical Imaging. J. Imaging Inform. Medicine 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
2024	J	`jnl`	Feasibility of Observing Cerebrovascular Disease Phenotypes with Smartphone Monitoring: Study Design Considerations for Real-World Studies. Sensors Stephanie Zawada, Ali Ganjizadeh, Clint E. Hagen, Bart M. Demaerschalk, Bradley J. Erickson
2024	J	`jnl`	Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. J. Imaging Inform. Medicine MM Zoghby, Bradley J. Erickson, Gian Marco Conte
2024	J	`jnl`	HOPPR Medical-Grade Platform for Medical Imaging AI. CoRR Kalina P. Slavkova, Melanie Traughber, Oliver Chen, Robert Bakos, Shayna Goldstein, Dan Harms, Bradley J. Erickson, Khan M. Siddiqui
2024	J	`jnl`	MedYOLO: A Medical Image Object Detection Framework. J. Imaging Inform. Medicine Joseph D. Sobek, Jose R. Medina Inojosa, Betsy J. Medina Inojosa, S. M. Rassoulinejad-Mousavi, Gian Marco Conte, Francisco Lopez-Jimenez, Bradley J. Erickson
2024	J	`jnl`	RadRotator: 3D Rotation of Radiographs with Diffusion Models. CoRR Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Kellen L. Mulford, Michael J. Taunton, Bradley J. Erickson, Cody C. Wyles
2024	J	`jnl`	Toward Clinically Trustworthy Deep Learning: Applying Conformal Prediction to Intracranial Hemorrhage Detection. CoRR Cooper U. Gamble, Shahriar Faghani, Bradley J. Erickson
2024	J	`jnl`	Visualizing Clinical Data Retrieval and Curation in Multimodal Healthcare AI Research: A Technical Note on RIL-workflow. J. Imaging Inform. Medicine Ali Ganjizadeh, Stephanie Zawada, Steve G. Langer, Bradley J. Erickson
2023	J	`jnl`	A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI. J. Digit. Imaging Shahriar Faghani, Bardia Khosravi, Mana Moassefi, Gian Marco Conte, Bradley J. Erickson
2023	J	`jnl`	Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study. J. Digit. Imaging Harrison C. Gottlich, Adriana V. Gregory, Vidit Sharma, Abhinav Khanna, Amr U. Moustafa, Christine M. Lohse, Theodora A. Potretzke, Panagiotis Korfiatis, Aaron M. Potretzke, Aleksandar Denic, Andrew D. Rule, Naoki Takahashi, Bradley J. Erickson, Bradley C. Leibovich, Timothy L. Kline
2023	J	`jnl`	Few-shot biomedical image segmentation using diffusion models: Beyond image generation. Comput. Methods Programs Biomed. Bardia Khosravi, Pouria Rouzrokh, John P. Mickley, Shahriar Faghani, Kellen L. Mulford, Linjun Yang, A. Noelle Larson, Benjamin M. Howe, Bradley J. Erickson, Michael J. Taunton, Cody C. Wyles
2023	J	`jnl`	MedYOLO: A Medical Image Object Detection Framework. CoRR Joseph D. Sobek, Jose R. Medina Inojosa, Betsy J. Medina Inojosa, S. M. Rassoulinejad-Mousavi, Gian Marco Conte, Francisco Lopez-Jimenez, Bradley J. Erickson
2023	J	`jnl`	Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. J. Imaging Inform. Medicine 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
2023	J	`jnl`	Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research. CoRR Bardia Khosravi, Frank Li, Theo Dapamede, Pouria Rouzrokh, Cooper U. Gamble, Hari M. Trivedi, Cody C. Wyles, Andrew B. Sellergren, Saptarshi Purkayastha, Bradley J. Erickson, Judy W. Gichoya
2022	—	`conf`	Betti-Number Based Machine-Learning Classifier Frame-work for Predicting the Hepatic Decompensation in Patients with Primary Sclerosing Cholangitis. CCWC Yashbir Singh, William Jons, Joseph D. Sobek, John E. Eaton, Bradley J. Erickson, Barrett J. Anderies, Jaidip Jagtap
2022	J	`jnl`	Deep Neural Network for Cardiac Magnetic Resonance Image Segmentation. J. Imaging David Chen, Huzefa M. Bhopalwala, Nakeya Dewaswala, Shivaram Poigai Arunachalam, Moein Enayati, Nasibeh Zanjirani Farahani, Kalyan Pasupathy, Sravani Lokineni, J. Martijn Bos, Peter A. Noseworthy, Reza Arsanjani, Bradley J. Erickson, Jeffrey B. Geske, Michael J. Ackerman, Philip A. Araoz, Adelaide M. Arruda-Olson
2022	J	`jnl`	Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report. CoRR Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Mana Moassefi, Sanaz Vahdati, Bradley J. Erickson
2021	J	`jnl`	Deep Learning Improves the Temporal Reproducibility of Aortic Measurement. J. Digit. Imaging Alex Bratt, Daniel J. Blezek, William J. Ryan, Kenneth A. Philbrick, Prabhakar Rajiah, Yasmeen K. Tandon, Lara A. Walkoff, Jason C. Cai, Emily N. Sheedy, Panagiotis Korfiatis, Eric E. Williamson, Bradley J. Erickson, Jeremy D. Collins
2021	—	`conf`	MRI Brain Tumor Segmentation Using Deep Encoder-Decoder Convolutional Neural Networks. BrainLes@MICCAI (2) 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
2021	J	`jnl`	SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks. CoRR Kuan Zhang, Haoji Hu, Kenneth Philbrick, Gian Marco Conte, Joseph D. Sobek, Pouria Rouzrokh, Bradley J. Erickson
2021	J	`jnl`	Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning. J. Digit. Imaging Adriana V. Gregory, Deema A. Anaam, Andrew J. Vercnocke, Marie E. Edwards, Vicente E. Torres, Peter C. Harris, Bradley J. Erickson, Timothy L. Kline
2020	J	`jnl`	Robust brain extraction tool for CT head images. Neurocomputing Zeynettin Akkus, Petro M. Kostandy, Kenneth A. Philbrick, Bradley J. Erickson
2019	J	`jnl`	Interactive segmentation of medical images through fully convolutional neural networks. CoRR Tomas Sakinis, Fausto Milletari, Holger Roth, Panagiotis Korfiatis, Petro M. Kostandy, Kenneth Philbrick, Zeynettin Akkus, Ziyue Xu, Daguang Xu, Bradley J. Erickson
2019	J	`jnl`	RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning. J. Digit. Imaging Kenneth A. Philbrick, Alexander D. Weston, Zeynettin Akkus, Timothy L. Kline, Panagiotis Korfiatis, Tomas Sakinis, Petro M. Kostandy, Arunnit Boonrod, Atefeh Zeinoddini, Naoki Takahashi, Bradley J. Erickson
2019	B	`conf`	Reduction of unnecessary thyroid biopsies using deep learning. Image Processing Zeynettin Akkus, Arunnit Boonrod, Mahfuzur R. Siddiquee, Kenneth A. Philbrick, Marius N. Stan, Regina M. Castro, Dana Erickson, Matthew R. Callstrom, Bradley J. Erickson
2018	J	`jnl`	Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. J. Digit. Imaging Youngoh Bae, Kunaraj Kumarasamy, Issa Ali, Panagiotis Korfiatis, Zeynettin Akkus, Bradley J. Erickson
2018	—	`conf`	Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients. Computer-Aided Diagnosis Panagiotis Korfiatis, Timothy L. Kline, Bradley J. Erickson
2018	B	`conf`	Extraction of brain tissue from CT head images using fully convolutional neural networks. Image Processing Zeynettin Akkus, Petro M. Kostandy, Kenneth A. Philbrick, Bradley J. Erickson
2017	J	`jnl`	Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. J. Digit. Imaging Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L. Rubin, Bradley J. Erickson
2017	J	`jnl`	Machine Learning: Discovering the Future of Medical Imaging. J. Digit. Imaging Bradley J. Erickson
2017	J	`jnl`	Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. J. Digit. Imaging Timothy L. Kline, Panagiotis Korfiatis, Marie E. Edwards, Jaime D. Blais, Frank S. Czerwiec, Peter C. Harris, Bernard F. King, Vicente E. Torres, Bradley J. Erickson
2017	J	`jnl`	Predicting Deletion of Chromosomal Arms 1p/19q in Low-Grade Gliomas from MR Images Using Machine Intelligence. J. Digit. Imaging Zeynettin Akkus, Issa Ali, Jirí Sedlár, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, Bradley J. Erickson
2017	J	`jnl`	Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. J. Digit. Imaging Panagiotis Korfiatis, Timothy L. Kline, Daniel H. Lachance, Ian F. Parney, Jan C. Buckner, Bradley J. Erickson
2017	J	`jnl`	Toolkits and Libraries for Deep Learning. J. Digit. Imaging Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick
2016	J	`jnl`	Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning. CoRR Zeynettin Akkus, Issa Ali, Jirí Sedlár, Timothy L. Kline, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, Bradley J. Erickson
2015	Misc	`conf`	The Best of Imaging Informatics Research 2015. AMIA Charles E. Kahn, Bradley J. Erickson
2014	B	`conf`	CT image noise reduction using rotational-invariant feature in Stockwell transform. Image Processing Jian Su, Zhoubo Li, Lifeng Yu, Joshua D. Warner, Daniel J. Blezek, Bradley J. Erickson
2014	Misc	`conf`	Effects of Wireless Signal Attenuation on Robot Team Performance. FLAIRS Briana Wellman, Bradley J. Erickson, Tommy Suriel, Kamala Mayo, Tajh Phifer, Kriti Acharya
2014	J	`jnl`	Supervised Segmentation of Polycystic Kidneys: a New Application for Stereology Data. J. Digit. Imaging Joshua D. Warner, Maria V. Irazabal, Ganapathy Krishnamurthi, Bernard F. King, Vicente E. Torres, Bradley J. Erickson
2014	J	`jnl`	Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer. Frontiers Neuroinformatics David A. Gutman, William D. Dunn, Jake Cobb, Richard Martin Stoner, Jayashree Kalpathy-Cramer, Bradley J. Erickson
2012	—	`conf`	Cluster-based differential features to improve detection accuracy of focal cortical dysplasia. Computer-Aided Diagnosis Chin-Ann Yang, Mostafa Kaveh, Bradley J. Erickson
2012	Misc	`conf`	Liver segmentation using structured sparse representations. ICASSP Vimal Singh, Dan Wang, Ahmed H. Tewfik, Bradley J. Erickson
2007	—	`conf`	Real-Time Mutual-Information-Based Linear Registration on the Cell Broadband Engine Processor. ISBI Moriyoshi Ohara, Hangu Yeo, Frank Savino, Giridharan Iyengar, Leiguang Gong, Hiroshi Inoue, Hideaki Komatsu, Vadim Sheinin, Shahrokh Daijavad, Bradley J. Erickson
2003	B	`conf`	Improved classification accuracy by feature extraction using genetic algorithms. Image Processing Julia Willamena Patriarche, Armando Manduca, Bradley J. Erickson
1997	B	`conf`	Clinical evaluation of wavelet compression of digitized chest x-rays. Image Processing Bradley J. Erickson, Armando Manduca, Kenneth R. Persons
1997	B	`conf`	Histogram transformation for improved compression of CT images. Image Processing Armando Manduca, Bradley J. Erickson, Kenneth R. Persons, Patrice M. Palisson
1997	B	`conf`	Integration of PACS image display with an electronic medical record. Image Processing Bradley J. Erickson, Dale G. Gehring, William J. Ryan
1996	B	`conf`	Automatic segmentation of MR brain images in multiple sclerosis patients. Image Processing Ramesh T. V. Avula, Bradley J. Erickson