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2020 – today
- 2024
[j50]Stephanie 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 24(11): 3595 (2024)- [i10]Cooper U. Gamble, Shahriar Faghani, Bradley J. Erickson:
Toward Clinically Trustworthy Deep Learning: Applying Conformal Prediction to Intracranial Hemorrhage Detection. CoRR abs/2401.08058 (2024) - [i9]Pouria Rouzrokh, Shahriar Faghani, Cooper U. Gamble, Moein Shariatnia, Bradley J. Erickson:
CONFLARE: CONFormal LArge language model REtrieval. CoRR abs/2404.04287 (2024) - [i8]Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Kellen L. Mulford, Michael J. Taunton, Bradley J. Erickson, Cody C. Wyles:
RadRotator: 3D Rotation of Radiographs with Diffusion Models. CoRR abs/2404.13000 (2024) - 2023
- [j49]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:
Few-shot biomedical image segmentation using diffusion models: Beyond image generation. Comput. Methods Programs Biomed. 242: 107832 (2023) - [j48]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. J. Digit. Imaging 36(3): 837-846 (2023) - [j47]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:
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 36(4): 1770-1781 (2023) - [j46]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:
Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. J. Imaging Inform. Medicine 36(5): 2306-2312 (2023) - [i7]David A. Clunie, Adam E. Flanders, Adam Taylor, Bradley James Erickson, Brian Bialecki, David Brundage, David Gutman, Fred W. Prior, J. Anthony Seibert, John H. Perry, Judy Wawira Gichoya, Justin S. Kirby, Katherine P. Andriole, Luke Geneslaw, Steve Moore, TJ Fitzgerald, Wyatt M. Tellis, Ying Xiao, Keyvan Farahani:
Report of the Medical Image De-Identification (MIDI) Task Group - Best Practices and Recommendations. CoRR abs/2303.10473 (2023) - [i6]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:
Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research. CoRR abs/2311.09402 (2023) - [i5]Joseph D. Sobek, Jose R. Medina Inojosa, Betsy J. Medina Inojosa, S. M. Rassoulinejad-Mousavi, Gian Marco Conte, Francisco Lopez-Jimenez, Bradley J. Erickson:
MedYOLO: A Medical Image Object Detection Framework. CoRR abs/2312.07729 (2023) - 2022
- [j45]Yashbir Singh, Naidu Subbarao, Abhinav Jaimini, Quincy A. Hathaway, Amina Kunovac, Bradley James Erickson, Vishnu Swarup, Himanshu Narayan Singh:
Genome-wide expression reveals potential biomarkers in breast cancer bone metastasis. J. Integr. Bioinform. 19(3) (2022) - [j44]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:
Deep Neural Network for Cardiac Magnetic Resonance Image Segmentation. J. Imaging 8(5): 149 (2022) - [c18]Yashbir Singh, William Jons, Joseph D. Sobek, John E. Eaton, Bradley J. Erickson, Barrett J. Anderies, Jaidip Jagtap:
Betti-Number Based Machine-Learning Classifier Frame-work for Predicting the Hepatic Decompensation in Patients with Primary Sclerosing Cholangitis. CCWC 2022: 159-162 - [i4]Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Mana Moassefi, Sanaz Vahdati, Bradley J. Erickson:
Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report. CoRR abs/2210.12113 (2022) - 2021
- [j43]Adriana V. Gregory, Deema A. Anaam, Andrew J. Vercnocke, Marie E. Edwards, Vicente E. Torres, Peter C. Harris, Bradley J. Erickson, Timothy L. Kline:
Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning. J. Digit. Imaging 34(4): 773-787 (2021) - [j42]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:
Deep Learning Improves the Temporal Reproducibility of Aortic Measurement. J. Digit. Imaging 34(5): 1183-1189 (2021) - [c17]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:
MRI Brain Tumor Segmentation Using Deep Encoder-Decoder Convolutional Neural Networks. BrainLes@MICCAI (2) 2021: 80-89 - [i3]Kuan Zhang, Haoji Hu, Kenneth Philbrick, Gian Marco Conte, Joseph D. Sobek, Pouria Rouzrokh, Bradley J. Erickson:
SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks. CoRR abs/2106.02599 (2021) - 2020
- [j41]Zeynettin Akkus, Petro M. Kostandy, Kenneth A. Philbrick, Bradley J. Erickson:
Robust brain extraction tool for CT head images. Neurocomputing 392: 189-195 (2020)
2010 – 2019
- 2019
- [j40]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:
RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning. J. Digit. Imaging 32(4): 571-581 (2019) - [c16]Zeynettin Akkus, Arunnit Boonrod, Mahfuzur R. Siddiquee, Kenneth A. Philbrick, Marius N. Stan, Regina M. Castro, Dana Erickson, Matthew R. Callstrom, Bradley J. Erickson:
Reduction of unnecessary thyroid biopsies using deep learning. Image Processing 2019: 109490W - [i2]Tomas Sakinis, Fausto Milletari, Holger Roth, Panagiotis Korfiatis, Petro M. Kostandy, Kenneth Philbrick, Zeynettin Akkus, Ziyue Xu, Daguang Xu, Bradley J. Erickson:
Interactive segmentation of medical images through fully convolutional neural networks. CoRR abs/1903.08205 (2019) - 2018
- [j39]Youngoh Bae, Kunaraj Kumarasamy, Issa Ali, Panagiotis Korfiatis, Zeynettin Akkus, Bradley J. Erickson:
Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. J. Digit. Imaging 31(2): 252-261 (2018) - [c15]Panagiotis Korfiatis, Timothy L. Kline, Bradley J. Erickson:
Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients. Computer-Aided Diagnosis 2018: 105752G - [c14]Zeynettin Akkus, Petro M. Kostandy, Kenneth A. Philbrick, Bradley J. Erickson:
Extraction of brain tissue from CT head images using fully convolutional neural networks. Image Processing 2018: 1057420 - 2017
- [j38]Christopher Meenan, Bradley James Erickson, Nancy Knight, Jewel Fossett, Elizabeth Olsen, Prerna Mohod, Joseph Chen, Steve G. Langer:
Workflow Lexicons in Healthcare: Validation of the SWIM Lexicon. J. Digit. Imaging 30(3): 255-266 (2017) - [j37]Bradley J. Erickson:
Machine Learning: Discovering the Future of Medical Imaging. J. Digit. Imaging 30(4): 391 (2017) - [j36]Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick:
Toolkits and Libraries for Deep Learning. J. Digit. Imaging 30(4): 400-405 (2017) - [j35]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:
Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. J. Digit. Imaging 30(4): 442-448 (2017) - [j34]Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L. Rubin, Bradley J. Erickson:
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. J. Digit. Imaging 30(4): 449-459 (2017) - [j33]Zeynettin Akkus, Issa Ali, Jirí Sedlár, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, Bradley J. Erickson:
Predicting Deletion of Chromosomal Arms 1p/19q in Low-Grade Gliomas from MR Images Using Machine Intelligence. J. Digit. Imaging 30(4): 469-476 (2017) - [j32]Panagiotis Korfiatis, Timothy L. Kline, Daniel H. Lachance, Ian F. Parney, Jan C. Buckner, Bradley J. Erickson:
Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. J. Digit. Imaging 30(5): 622-628 (2017) - 2016
- [i1]Zeynettin Akkus, Issa Ali, Jirí Sedlár, Timothy L. Kline, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, Bradley J. Erickson:
Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning. CoRR abs/1611.06939 (2016) - 2015
- [j31]Steve G. Langer, Wyatt M. Tellis, Chris Carr, Mark Daly, Bradley James Erickson, David S. Mendelson, S. Moore, J. Perry, K. Shastri, Max Warnock, W. Zhu:
The RSNA Image Sharing Network. J. Digit. Imaging 28(1): 53-61 (2015) - [c13]Charles E. Kahn, Bradley J. Erickson:
The Best of Imaging Informatics Research 2015. AMIA 2015 - 2014
- [j30]David A. Gutman, William D. Dunn, Jake Cobb, Richard Martin Stoner, Jayashree Kalpathy-Cramer, Bradley J. Erickson:
Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer. Frontiers Neuroinformatics 8: 53 (2014) - [j29]Bradley James Erickson, Steve G. Langer, Daniel J. Blezek, William J. Ryan, Todd French:
DEWEY: The DICOM-Enabled Workflow Engine System. J. Digit. Imaging 27(3): 309-313 (2014) - [j28]Joshua D. Warner, Maria V. Irazabal, Ganapathy Krishnamurthi, Bernard F. King, Vicente E. Torres, Bradley J. Erickson:
Supervised Segmentation of Polycystic Kidneys: a New Application for Stereology Data. J. Digit. Imaging 27(4): 514-519 (2014) - [j27]William F. Styler IV, Steven Bethard, Sean Finan, Martha Palmer, Sameer Pradhan, Piet C. de Groen, Bradley James Erickson, Timothy A. Miller, Chen Lin, Guergana K. Savova, James Pustejovsky:
Temporal Annotation in the Clinical Domain. Trans. Assoc. Comput. Linguistics 2: 143-154 (2014) - [c12]Briana Wellman, Bradley J. Erickson, Tommy Suriel, Kamala Mayo, Tajh Phifer, Kriti Acharya:
Effects of Wireless Signal Attenuation on Robot Team Performance. FLAIRS 2014 - [c11]Jian Su, Zhoubo Li, Lifeng Yu, Joshua D. Warner, Daniel J. Blezek, Bradley J. Erickson:
CT image noise reduction using rotational-invariant feature in Stockwell transform. Image Processing 2014: 903433 - 2013
- [j26]Bradley James Erickson, Christopher Meenan, Steve Langer:
Standards for Business Analytics and Departmental Workflow. J. Digit. Imaging 26(1): 53-57 (2013) - [j25]Steve G. Langer, Kenneth R. Persons, Bradley James Erickson, Daniel J. Blezek:
Towards a More Cloud-Friendly Medical Imaging Applications Architecture: A Modest Proposal. J. Digit. Imaging 26(1): 58-64 (2013) - 2012
- [j24]Bradley James Erickson, Tony Pan, Daniel S. Marcus:
Whitepapers on Imaging Infrastructure for Research - Part 1: General Workflow Considerations. J. Digit. Imaging 25(4): 449-453 (2012) - [j23]Daniel S. Marcus, Bradley James Erickson, Tony Pan:
Imaging Infrastructure for Research. Part 2. Data Management Practices. J. Digit. Imaging 25(5): 566-569 (2012) - [j22]Tony Pan, Bradley James Erickson, Daniel S. Marcus:
Whitepapers on Imaging Infrastructure for Research Part Three: Security and Privacy. J. Digit. Imaging 25(6): 692-702 (2012) - [c10]Vimal Singh, Dan Wang, Ahmed H. Tewfik, Bradley J. Erickson:
Liver segmentation using structured sparse representations. ICASSP 2012: 565-568 - [c9]Chin-Ann Yang, Mostafa Kaveh, Bradley J. Erickson:
Cluster-based differential features to improve detection accuracy of focal cortical dysplasia. Computer-Aided Diagnosis 2012: 83151G - 2011
- [j21]Xiaojiang Yang, Daniel J. Blezek, Lionel Tim-Ee Cheng, William J. Ryan, David F. Kallmes, Bradley James Erickson:
Computer-Aided Detection of Intracranial Aneurysms in MR Angiography. J. Digit. Imaging 24(1): 86-95 (2011) - [j20]Bradley James Erickson:
Experience with Importation of Electronic Images into the Medical Record from Physical Media. J. Digit. Imaging 24(4): 694-699 (2011) - [c8]Chin-Ann Yang, Mostafa Kaveh, Bradley James Erickson:
Automated detection of Focal Cortical Dysplasia lesions on T1-weighted MRI using volume-based distributional features. ISBI 2011: 865-870 - 2010
- [j19]Daniel J. Blezek, David G. Carlson, Lionel Tim-Ee Cheng, Jared A. Christensen, Matthew R. Callstrom, Bradley James Erickson:
Cell Accelerated Cryoablation Simulation. Comput. Methods Programs Biomed. 98(3): 241-252 (2010) - [j18]Lionel Tim-Ee Cheng, Jiaping Zheng, Guergana K. Savova, Bradley James Erickson:
Discerning Tumor Status from Unstructured MRI Reports - Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing. J. Digit. Imaging 23(2): 119-132 (2010) - [j17]Bradley James Erickson, Elizabeth A. Krupinski, Katherine P. Andriole:
A Multicenter Observer Performance Study of 3D JPEG2000 Compression of Thin-Slice CT. J. Digit. Imaging 23(5): 639-643 (2010)
2000 – 2009
- 2009
- [c7]Zachary Kelm, Daniel J. Blezek, Brian J. Bartholmai, Bradley James Erickson:
Optimizing Non-Local Means for Denoising Low Dose CT. ISBI 2009: 662-665 - 2007
- [j16]Bradley James Erickson, Jayawant Mandrekar, Liqin Wang, Julia Willamena Patriarche, Brian J. Bartholmai, Christropher P. Wood, E. Paul Lindell, Anne-Marie Sykes, Gordon F. Harms, Rebecca M. Lindell, Katherine P. Andriole:
Effect of Automated Image Registration on Radiologist Interpretation. J. Digit. Imaging 20(2): 105-113 (2007) - [j15]Julia Willamena Patriarche, Bradley James Erickson:
Part 1. Automated Change Detection and Characterization in Serial MR Studies of Brain-Tumor Patients. J. Digit. Imaging 20(3): 203-222 (2007) - [j14]Julia Willamena Patriarche, Bradley James Erickson:
Part 2. Automated Change Detection and Characterization Applied to Serial MR of Brain Tumors may Detect Progression Earlier than Human Experts. J. Digit. Imaging 20(4): 321-328 (2007) - [c6]Moriyoshi Ohara, Hangu Yeo, Frank Savino, Giridharan Iyengar, Leiguang Gong, Hiroshi Inoue, Hideaki Komatsu, Vadim Sheinin, Shahrokh Daijavad, Bradley J. Erickson:
Real-Time Mutual-Information-Based Linear Registration on the Cell Broadband Engine Processor. ISBI 2007: 33-36 - 2004
- [j13]Steve Langer, Brian J. Bartholmai, Kenneth A. Fetterly, Scott Harmsen, William J. Ryan, Bradley James Erickson, Katherine P. Andriole, John A. Carrino:
SCAR R&D Symposium 2003: Comparing the Efficacy of 5-MP CRT Versus 3-MP LCD in the Evaluation of Interstitial Lung Disease. J. Digit. Imaging 17(3): 149-157 (2004) - [j12]Julia Willamena Patriarche, Bradley James Erickson:
A Review of the Automated Detection of Change in Serial Imaging Studies of the Brain. J. Digit. Imaging 17(3): 158-174 (2004) - [j11]Katherine P. Andriole, Richard L. Morin, Ronald L. Arenson, John A. Carrino, Bradley James Erickson, Steven C. Horii, David W. Piraino, Bruce I. Reiner, J. Anthony Seibert, Eliot L. Siegel:
Addressing the Coming Radiology Crisis - The Society for Computer Applications in Radiology Transforming the Radiological Interpretation Process (TRIPTM) Initiative. J. Digit. Imaging 17(4): 235-243 (2004) - 2003
- [j10]Shawn P. Laird, Johnny S. Wong, William J. Schaller, Bradley James Erickson, Piet C. de Groen:
Design and implementation of an Internet-based medical image viewing system. J. Syst. Softw. 66(2): 167-181 (2003) - [c5]Julia Willamena Patriarche, Armando Manduca, Bradley J. Erickson:
Improved classification accuracy by feature extraction using genetic algorithms. Image Processing 2003 - 2002
- [j9]Bradley James Erickson:
Irreversible Compression of Medical Images. J. Digit. Imaging 15(1): 5-14 (2002) - [j8]Kenneth R. Persons, Nicholas J. Hangiandreou, Nicholas T. Charboneau, J. Charboneau, E. Meredith James, Bruce R. Douglas, Ann P. Salmon, John M. Knudsen, Bradley James Erickson:
Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice. J. Digit. Imaging 15(1): 15-21 (2002) - [j7]Bradley James Erickson, Kenneth R. Persons, Nicholas J. Hangiandreou, E. Meredith James, Christopher J. Hanna, Dale G. Gehring:
Requirements for an Enterprise Digital Image Archive. J. Digit. Imaging 15(1): 72-82 (2002) - [j6]Bradley James Erickson, Brian J. Bartholmai:
Computer-Aided Detection and Diagnosis at the Start of the Third Millennium. J. Digit. Imaging 15(2): 59-68 (2002) - [j5]Bradley James Erickson, Brian A. Cole, John Huston:
Semiautomated Quantitation of Carotid Artery Stenosis in Gadolinium-Bolus Magnetic Resonance Angiography. J. Digit. Imaging 15(2): 69-77 (2002) - 2001
- [j4]Kalpana M. Kanal, Nicholas J. Hangiandreou, Anne-Marie Sykes, H. E. Eklund, P. A. Araoz, J. A. Leon, Bradley James Erickson:
Initial evaluation of a continuous speech recognition program for radiology. J. Digit. Imaging 14(1): 30-37 (2001) - 2000
- [j3]Kenneth R. Persons, Patrice Palisson, Armando Manduca, William J. Charboneau, E. Meredith James, Nicholas T. Charboneau, Nicholas J. Hangiandreou, Bradley James Erickson:
Ultrasound grayscale image compression with JPEG and wavelet techniques. J. Digit. Imaging 13(1): 25-32 (2000)
1990 – 1999
- 1998
- [j2]Bradley James Erickson, Ramesh T. V. Avula:
An algorithm for automatic segmentation and classification of magnetic resonance brain images. J. Digit. Imaging 11(2): 74-82 (1998) - 1997
- [j1]Bradley James Erickson, Armando Manduca, Kenneth R. Persons, Frank Earnest, Thomas E. Hartman, Gordon F. Harms, Larry R. Brown:
Evaluation of irreversible compression of digitized posterior-anterior chest radiographs. J. Digit. Imaging 10(3): 97-102 (1997) - [c4]Bradley J. Erickson, Dale G. Gehring, William J. Ryan:
Integration of PACS image display with an electronic medical record. Image Processing 1997 - [c3]Bradley J. Erickson, Armando Manduca, Kenneth R. Persons:
Clinical evaluation of wavelet compression of digitized chest x-rays. Image Processing 1997 - [c2]Armando Manduca, Bradley J. Erickson, Kenneth R. Persons, Patrice M. Palisson:
Histogram transformation for improved compression of CT images. Image Processing 1997 - 1996
- [c1]Ramesh T. V. Avula, Bradley J. Erickson:
Automatic segmentation of MR brain images in multiple sclerosis patients. Image Processing 1996
Coauthor Index
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