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Journal Articles
- 2024
[j28]Yixin Zhang
, Maciej A. Mazurowski:
Convolutional neural networks rarely learn shape for semantic segmentation. Pattern Recognit. 146: 110018 (2024)- 2023
- [j27]Jikai Zhang, Maciej A. Mazurowski, Brian C. Allen, Benjamin Wildman-Tobriner:
Multistep Automated Data Labelling Procedure (MADLaP) for thyroid nodules on ultrasound: An artificial intelligence approach for automating image annotation. Artif. Intell. Medicine 141: 102553 (2023) - [j26]Shixing Cao, Nicholas Konz, James S. Duncan, Maciej A. Mazurowski:
Deep Learning for Breast MRI Style Transfer with Limited Training Data. J. Digit. Imaging 36(2): 666-678 (2023) - [j25]Jikai Zhang, Carlos Santos, Christine Park, Maciej A. Mazurowski, Roy J. Colglazier:
Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach. J. Digit. Imaging 36(6): 2402-2410 (2023) - [j24]Nicholas Konz, Haoyu Dong, Maciej A. Mazurowski:
Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion. Medical Image Anal. 87: 102836 (2023) - [j23]Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, Yixin Zhang:
Segment anything model for medical image analysis: An experimental study. Medical Image Anal. 89: 102918 (2023) - [j22]Haoyu Dong, Yifan Zhang, Hanxue Gu, Nicholas Konz, Yixin Zhang, Maciej A. Mazurowski:
SWSSL: Sliding Window-Based Self-Supervised Learning for Anomaly Detection in High-Resolution Images. IEEE Trans. Medical Imaging 42(12): 3860-3870 (2023) - 2022
- [j21]Vincent M. D'Anniballe, Fakrul Islam Tushar, Khrystyna Faryna, Songyue Han, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo:
Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning. BMC Medical Informatics Decis. Mak. 22(1): 102 (2022) - [j20]Zhe Zhu, Amber Mittendorf, Erin Shropshire, Brian C. Allen, Chad M. Miller, Mustafa R. Bashir, Maciej A. Mazurowski:
3D Pyramid Pooling Network for Abdominal MRI Series Classification. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 1688-1698 (2022) - [j19]Rui Hou, Yifan Peng, Lars J. Grimm, Yinhao Ren, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Anomaly Detection of Calcifications in Mammography Based on 11, 000 Negative Cases. IEEE Trans. Biomed. Eng. 69(5): 1639-1650 (2022) - 2021
- [j18]Albert Swiecicki, Nianyi Li, Jonathan O'Donnell, Nicholas Said, Jichen Yang, Richard C. Mather, William A. Jiranek, Maciej A. Mazurowski:
Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists. Comput. Biol. Medicine 133: 104334 (2021) - [j17]Gourav Modanwal, Adithya Vellal, Maciej A. Mazurowski:
Normalization of breast MRIs using cycle-consistent generative adversarial networks. Comput. Methods Programs Biomed. 208: 106225 (2021) - [j16]Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin:
Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes. Medical Image Anal. 67: 101857 (2021) - 2020
- [j15]Rui Hou, Maciej A. Mazurowski, Lars J. Grimm, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation. IEEE Trans. Biomed. Eng. 67(6): 1565-1572 (2020) - 2019
- [j14]Zhe Zhu, Ehab Albadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski:
Deep learning for identifying radiogenomic associations in breast cancer. Comput. Biol. Medicine 109: 85-90 (2019) - [j13]Mateusz Buda, Ashirbani Saha, Maciej A. Mazurowski:
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm. Comput. Biol. Medicine 109: 218-225 (2019) - [j12]Zhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, Eun-Sil Shelley Hwang, Maciej A. Mazurowski:
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ. Comput. Biol. Medicine 115 (2019) - [j11]Jun Zhang, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski:
Hierarchical Convolutional Neural Networks for Segmentation of Breast Tumors in MRI With Application to Radiogenomics. IEEE Trans. Medical Imaging 38(2): 435-447 (2019) - 2018
- [j10]Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski:
A systematic study of the class imbalance problem in convolutional neural networks. Neural Networks 106: 249-259 (2018) - 2017
- [j9]Ashirbani Saha, Xiaozhi Yu, Dushyant Sahoo, Maciej A. Mazurowski:
Effects of MRI scanner parameters on breast cancer radiomics. Expert Syst. Appl. 87: 384-391 (2017) - 2016
- [j8]Mengyu Wang, Jing Zhang, Lars J. Grimm, Sujata V. Ghate, Ruth Walsh, Karen S. Johnson, Joseph Y. Lo, Maciej A. Mazurowski:
Predicting false negative errors in digital breast tomosynthesis among radiology trainees using a computer vision-based approach. Expert Syst. Appl. 56: 1-8 (2016) - [j7]Mengyu Wang, Meng Wang, Lars J. Grimm, Maciej A. Mazurowski:
A computer vision-based algorithm to predict false positive errors in radiology trainees when interpreting digital breast tomosynthesis cases. Expert Syst. Appl. 64: 490-499 (2016) - 2015
- [j6]Jing Zhang, James I. Silber, Maciej A. Mazurowski:
Modeling false positive error making patterns in radiology trainees for improved mammography education. J. Biomed. Informatics 54: 50-57 (2015) - 2013
- [j5]Maciej A. Mazurowski:
Estimating confidence of individual rating predictions in collaborative filtering recommender systems. Expert Syst. Appl. 40(10): 3847-3857 (2013) - 2012
- [j4]Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi:
The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support. Neural Networks 25: 141-145 (2012) - 2011
- [j3]Maciej A. Mazurowski, Joseph Y. Lo, Brian P. Harrawood, Georgia D. Tourassi:
Mutual information-based template matching scheme for detection of breast masses: From mammography to digital breast tomosynthesis. J. Biomed. Informatics 44(5): 815-823 (2011) - 2009
- [j2]Jacek M. Zurada, Maciej A. Mazurowski, Rommohan Ragade, Artur Abdullin, Janusz Wojtusiak, James E. Gentle:
Building virtual community in computational intelligence and machine learning [Research Frontier]. IEEE Comput. Intell. Mag. 4(1): 43-54 (2009) - 2008
- [j1]Maciej A. Mazurowski, Piotr A. Habas, Jacek M. Zurada, Joseph Y. Lo, Jay A. Baker, Georgia D. Tourassi:
Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance. Neural Networks 21(2-3): 427-436 (2008)
Conference and Workshop Papers
- 2024
- [c46]Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej A. Mazurowski:
Medical Image Segmentation with InTEnt: Integrated Entropy Weighting for Single Image Test-Time Adaptation. CVPR Workshops 2024: 5046-5055 - [c45]Nicholas Konz, Maciej A. Mazurowski:
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images. ICLR 2024 - [c44]Nicholas Konz, Yuwen Chen, Haoyu Dong, Maciej A. Mazurowski:
Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models. MICCAI (7) 2024: 88-98 - 2023
- [c43]Hanxue Gu, Hongyu He, Roy J. Colglazier, Jordan Axelrod, Robert French, Maciej A. Mazurowski:
SuperMask: Generating High-resolution object masks from multi-view, unaligned low-resolution MRIs. MIDL 2023: 119-133 - [c42]Nicholas Konz, Maciej A. Mazurowski:
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images. MIDL 2023: 829-845 - 2022
- [c41]Fakrul Islam Tushar, Ehsan Abadi, Saman Sotoudeh-Paima, Rafael B. Fricks, Maciej A. Mazurowski, William Paul Segars, Ehsan Samei, Joseph Y. Lo:
Virtual vs. reality: external validation of COVID-19 classifiers using XCAT phantoms for chest computed tomography. Medical Imaging: Computer-Aided Diagnosis 2022 - [c40]Yifan Zhang, Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej A. Mazurowski:
Lightweight Transformer Backbone for Medical Object Detection. CaPTion@MICCAI 2022: 47-56 - [c39]Nicholas Konz, Hanxue Gu, Haoyu Dong, Maciej A. Mazurowski:
The Intrinsic Manifolds of Radiological Images and Their Role in Deep Learning. MICCAI (8) 2022: 684-694 - 2021
- [c38]Zhe Zhu, Mustafa R. Bashir, Maciej A. Mazurowski:
Deep neural networks trained for segmentation are sensitive to brightness changes: preliminary results. Medical Imaging: Computer-Aided Diagnosis 2021 - 2020
- [c37]Rui Hou, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
A multitask deep learning method in simultaneously predicting occult invasive disease in ductal carcinoma in-situ and segmenting microcalcifications in mammography. Medical Imaging: Computer-Aided Diagnosis 2020 - [c36]Nianyi Li, Albert Swiecicki, Nicholas Said, Jonathan O'Donnell, William A. Jiranek, Maciej A. Mazurowski:
Automatic Kellgren-Lawrence grade estimation driven deep learning algorithms. Medical Imaging: Computer-Aided Diagnosis 2020 - [c35]Gourav Modanwal, Adithya Vellal, Mateusz Buda, Maciej A. Mazurowski:
MRI image harmonization using cycle-consistent generative adversarial network. Medical Imaging: Computer-Aided Diagnosis 2020 - [c34]Anindo Saha, Fakrul Islam Tushar, Khrystyna Faryna, Vincent M. D'Anniballe, Rui Hou, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo:
Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features. Medical Imaging: Computer-Aided Diagnosis 2020 - [c33]Albert Swiecicki, Mateusz Buda, Ashirbani Saha, Nianyi Li, Sujata V. Ghate, Ruth Walsh, Maciej A. Mazurowski:
Generative adversarial network-based image completion to identify abnormal locations in digital breast tomosynthesis images. Medical Imaging: Computer-Aided Diagnosis 2020 - [c32]Albert Swiecicki, Nicholas Said, Jonathan O'Donnell, Mateusz Buda, Nianyi Li, William A. Jiranek, Maciej A. Mazurowski:
Automatic estimation of knee joint space narrowing by deep learning segmentation algorithms. Medical Imaging: Computer-Aided Diagnosis 2020 - 2019
- [c31]Matias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao:
Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports. Medical Imaging: Computer-Aided Diagnosis 2019: 109500V - [c30]Rui Hou, Yinhao Ren, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Malignant microcalcification clusters detection using unsupervised deep autoencoders. Medical Imaging: Computer-Aided Diagnosis 2019: 109502Q - 2018
- [c29]Rui Hou, Bibo Shi, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Improving classification with forced labeling of other related classes: application to prediction of upstaged ductal carcinoma in situ using mammographic features. Medical Imaging: Computer-Aided Diagnosis 2018: 105750R - [c28]Jun Zhang, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski:
Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomics. Medical Imaging: Computer-Aided Diagnosis 2018: 105750U - [c27]Bibo Shi, Rui Hou, Maciej A. Mazurowski, Lars J. Grimm, Yinhao Ren, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning. Medical Imaging: Computer-Aided Diagnosis 2018: 105752R - [c26]Jun Zhang, Sujata V. Ghate, Lars J. Grimm, Ashirbani Saha, Elizabeth Hope Cain, Zhe Zhu, Maciej A. Mazurowski:
Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis. Medical Imaging: Computer-Aided Diagnosis 2018: 105752V - [c25]Zhe Zhu, Ehab Albadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski:
Breast cancer molecular subtype classification using deep features: preliminary results. Medical Imaging: Computer-Aided Diagnosis 2018: 105752X - [c24]Zhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, Eun-Sil Shelley Hwang, Maciej A. Mazurowski:
Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data. Medical Imaging: Computer-Aided Diagnosis 2018: 105752W - [c23]Ashirbani Saha, Michael R. Harowicz, Lars J. Grimm, Connie E. Kim, Ruth Walsh, Sujata V. Ghate, Maciej A. Mazurowski:
Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluation. Medical Imaging: Computer-Aided Diagnosis 2018: 1057507 - [c22]Jun Zhang, Elizabeth Hope Cain, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski:
Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regression. Medical Imaging: Computer-Aided Diagnosis 2018: 1057525 - 2017
- [c21]Maciej A. Mazurowski, Kal Clark, Nicholas M. Czarnek, Parisa Shamsesfandabadi, Katherine B. Peters, Ashirbani Saha:
Radiogenomic analysis of lower grade glioma: a pilot multi-institutional study shows an association between quantitative image features and tumor genomics. Medical Imaging: Computer-Aided Diagnosis 2017: 101341T - [c20]David Paredes, Ashirbani Saha, Maciej A. Mazurowski:
Deep learning for segmentation of brain tumors: can we train with images from different institutions? Medical Imaging: Computer-Aided Diagnosis 2017: 101341P - [c19]Bibo Shi, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features. Medical Imaging: Computer-Aided Diagnosis 2017: 101341I - [c18]Bibo Shi, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features? Medical Imaging: Computer-Aided Diagnosis 2017: 101342X - 2016
- [c17]Nicholas M. Czarnek, Kal Clark, Katherine B. Peters, Leslie M. Collins, Maciej A. Mazurowski:
Radiogenomics of glioblastoma: a pilot multi-institutional study to investigate a relationship between tumor shape features and tumor molecular subtype. Medical Imaging: Computer-Aided Diagnosis 2016: 97850V - [c16]Maciej A. Mazurowski, Nicholas M. Czarnek, Leslie M. Collins, Katherine B. Peters, Kal Clark:
Predicting outcomes in glioblastoma patients using computerized analysis of tumor shape: preliminary data. Medical Imaging: Computer-Aided Diagnosis 2016: 97852T - [c15]Mengyu Wang, Jing Zhang, Lars J. Grimm, Sujata V. Ghate, Ruth Walsh, Karen S. Johnson, Joseph Y. Lo, Maciej A. Mazurowski:
Identification of error making patterns in lesion detection on digital breast tomosynthesis using computer-extracted image features. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2016: 978709 - 2010
- [c14]Georgia D. Tourassi, Maciej A. Mazurowski, Elizabeth A. Krupinski:
Perception-driven IT-CADe analysis for the detection of masses in screening mammography: initial investigation. Medical Imaging: Computer-Aided Diagnosis 2010: 762406 - 2009
- [c13]Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi:
The effect of class imbalance on case selection for case-based classifiers, with emphasis on computer-aided diagnosis systems. IJCNN 2009: 1975-1980 - [c12]Maciej A. Mazurowski, Georgia D. Tourassi:
Evaluating classifiers: Relation between area under the receiver operator characteristic curve and overall accuracy. IJCNN 2009: 2045-2049 - [c11]Maciej A. Mazurowski, Jordan M. Malof, Jacek M. Zurada, Georgia D. Tourassi:
A comparative study of database reduction methods for case-based computer-aided detection systems: preliminary results. Medical Imaging: Computer-Aided Diagnosis 2009: 72600F - [c10]Maciej A. Mazurowski, Georgia D. Tourassi:
Relational representation for improved decisions with an information-theoretic CADe system: initial experience. Medical Imaging: Computer-Aided Diagnosis 2009: 726018 - 2008
- [c9]Jacek M. Zurada, Janusz Wojtusiak, Fahmida Chowdhury, James E. Gentle, Cedric J. Jeannot, Maciej A. Mazurowski:
Computational intelligence virtual community: Framework and implementation issues. IJCNN 2008: 3153-3157 - [c8]Maciej A. Mazurowski, Jacek M. Zurada, Georgia D. Tourassi:
Reliability Assessment of Ensemble Classifiers: Application in Mammography. Digital Mammography / IWDM 2008: 366-370 - [c7]Maciej A. Mazurowski, Jacek M. Zurada, Georgia D. Tourassi:
Database decomposition of a knowledge-based CAD system in mammography: an ensemble approach to improve detection. Medical Imaging: Computer-Aided Diagnosis 2008: 69151K - 2007
- [c6]Maciej A. Mazurowski, Piotr A. Habas, Georgia D. Tourassi, Jacek M. Zurada:
Case-base reduction for a computer assisted breast cancer detection system using genetic algorithms. IEEE Congress on Evolutionary Computation 2007: 600-605 - [c5]Maciej A. Mazurowski, Jacek M. Zurada:
Solving decentralized multi-agent control problems with genetic algorithms. IEEE Congress on Evolutionary Computation 2007: 1029-1034 - [c4]Georgia D. Tourassi, Jonathan L. Jesneck, Maciej A. Mazurowski, Piotr A. Habas:
Stacked Generalization in Computer-Assisted Decision Systems: Empirical Comparison of Data Handling Schemes. IJCNN 2007: 1343-1347 - [c3]Maciej A. Mazurowski, Piotr A. Habas, Georgia D. Tourassi, Jacek M. Zurada:
Impact of Low Class Prevalence on the Performance Evaluation of Neural Network Based Classifiers: Experimental Study in the Context of Computer-Assisted Medical Diagnosis. IJCNN 2007: 2005-2009 - [c2]Maciej A. Mazurowski, Jacek M. Zurada:
Solving Multi-agent Control Problems Using Particle Swarm Optimization. SIS 2007: 105-111 - 2005
- [c1]Przemyslaw Szecówka, Andrzej Szczurek, Maciej A. Mazurowski, Benedykt Licznerski, Franz Pichler:
Neural Network Sensitivity Analysis Applied for the Reduction of the Sensor Matrix. EUROCAST 2005: 27-32
Editorship
- 2021
- [e2]Maciej A. Mazurowski, Karen Drukker:
Medical Imaging 2021: Computer-Aided Diagnosis, Online, February 15-20, 2021. SPIE Proceedings 11597, SPIE 2021, ISBN 9781510640238 [contents] - 2020
- [e1]Horst K. Hahn, Maciej A. Mazurowski:
Medical Imaging 2020: Computer-Aided Diagnosis, Houston, TX, USA, February 16-19, 2020. SPIE Proceedings 11314, SPIE 2020, ISBN 9781510633957 [contents]
Informal and Other Publications
- 2024
- [i44]Nicholas Konz, Maciej A. Mazurowski:
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images. CoRR abs/2401.08865 (2024) - [i43]Hanxue Gu, Roy J. Colglazier, Haoyu Dong, Jikai Zhang, Yaqian Chen, Zafer Yildiz, Yuwen Chen, Lin Li, Jichen Yang, Jay Willhite, Alex M. Meyer, Brian Guo, Yashvi Atul Shah, Emily Luo, Shipra Rajput, Sally Kuehn, Clark Bulleit, Kevin A. Wu, Jisoo Lee, Brandon Ramirez, Darui Lu, Jay M. Levin, Maciej A. Mazurowski:
SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI. CoRR abs/2401.12974 (2024) - [i42]Nicholas Konz, Yuwen Chen, Haoyu Dong, Maciej A. Mazurowski:
Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models. CoRR abs/2402.05210 (2024) - [i41]Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej A. Mazurowski:
Medical Image Segmentation with InTEnt: Integrated Entropy Weighting for Single Image Test-Time Adaptation. CoRR abs/2402.09604 (2024) - [i40]Yuwen Chen, Nicholas Konz, Hanxue Gu, Haoyu Dong, Yaqian Chen, Lin Li, Jisoo Lee, Maciej A. Mazurowski:
ContourDiff: Unpaired Image Translation with Contour-Guided Diffusion Models. CoRR abs/2403.10786 (2024) - [i39]Keyu Li, Hanxue Gu, Roy J. Colglazier, Robert Lark, Elizabeth Hubbard, Robert French, Denise Smith, Jikai Zhang, Erin McCrum, Anthony Catanzano, Joseph Cao, Leah Waldman, Maciej A. Mazurowski, Benjamin Alman:
Deep learning automates Cobb angle measurement compared with multi-expert observers. CoRR abs/2403.12115 (2024) - [i38]Nicholas Konz, Yuwen Chen, Hanxue Gu, Haoyu Dong, Maciej A. Mazurowski:
Rethinking Perceptual Metrics for Medical Image Translation. CoRR abs/2404.07318 (2024) - [i37]Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej A. Mazurowski:
How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model. CoRR abs/2404.09957 (2024) - [i36]Haoyu Dong, Hanxue Gu, Yaqian Chen, Jichen Yang, Yuwen Chen, Maciej A. Mazurowski:
Segment anything model 2: an application to 2D and 3D medical images. CoRR abs/2408.00756 (2024) - [i35]Nicholas Konz, Maciej A. Mazurowski:
Pre-processing and Compression: Understanding Hidden Representation Refinement Across Imaging Domains via Intrinsic Dimension. CoRR abs/2408.08381 (2024) - [i34]Zafer Yildiz, Yuwen Chen, Maciej A. Mazurowski:
SAM & SAM 2 in 3D Slicer: SegmentWithSAM Extension for Annotating Medical Images. CoRR abs/2408.15224 (2024) - [i33]Gregory Szumel, Brian Guo, Darui Lu, Rongze Gui, Tingyu Wang, Nicholas Konz, Maciej A. Mazurowski:
The Impact of Scanner Domain Shift on Deep Learning Performance in Medical Imaging: an Experimental Study. CoRR abs/2409.04368 (2024) - [i32]Mohamed Sobhi Jabal, Pranav I. Warman, Jikai Zhang, Kartikeye Gupta, Ayush Jain, Maciej A. Mazurowski, Walter F. Wiggins, Kirti Magudia, Evan Calabrese:
Language Models and Retrieval Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports. CoRR abs/2409.10576 (2024) - 2023
- [i31]Shixing Cao, Nicholas Konz, James S. Duncan, Maciej A. Mazurowski:
Deep Learning for Breast MRI Style Transfer with Limited Training Data. CoRR abs/2301.02069 (2023) - [i30]Nicholas Konz, Maciej A. Mazurowski:
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images. CoRR abs/2303.04911 (2023) - [i29]Hanxue Gu, Hongyu He, Roy J. Colglazier, Jordan Axelrod, Robert French, Maciej A. Mazurowski:
SuperMask: Generating High-resolution object masks from multi-view, unaligned low-resolution MRIs. CoRR abs/2303.07517 (2023) - [i28]Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, Yixin Zhang:
Segment Anything Model for Medical Image Analysis: an Experimental Study. CoRR abs/2304.10517 (2023) - [i27]Nicholas Konz, Haoyu Dong, Maciej A. Mazurowski:
Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion. CoRR abs/2305.03098 (2023) - [i26]Yixin Zhang, Maciej A. Mazurowski:
Convolutional Neural Networks Rarely Learn Shape for Semantic Segmentation. CoRR abs/2305.06568 (2023) - [i25]Hanxue Gu, Haoyu Dong, Nicholas Konz, Maciej A. Mazurowski:
A systematic study of the foreground-background imbalance problem in deep learning for object detection. CoRR abs/2306.16539 (2023) - [i24]Jikai Zhang, Carlos Santos, Christine Park, Maciej A. Mazurowski, Roy J. Colglazier:
Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach. CoRR abs/2309.02681 (2023) - [i23]Jee Seok Yoon, Kwanseok Oh, Yooseung Shin, Maciej A. Mazurowski, Heung-Il Suk:
Domain Generalization for Medical Image Analysis: A Survey. CoRR abs/2310.08598 (2023) - [i22]Yixin Zhang, Shen Zhao, Hanxue Gu, Maciej A. Mazurowski:
How to Efficiently Annotate Images for Best-Performing Deep Learning Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model. CoRR abs/2312.10600 (2023) - 2022
- [i21]Fakrul Islam Tushar, Husam Nujaim, Wanyi Fu, Ehsan Abadi, Maciej A. Mazurowski, Ehsan Samei, William Paul Segars, Joseph Y. Lo:
Quality or Quantity: Toward a Unified Approach for Multi-organ Segmentation in Body CT. CoRR abs/2203.01934 (2022) - [i20]Fakrul Islam Tushar, Ehsan Abadi, Saman Sotoudeh-Paima, Rafael B. Fricks, Maciej A. Mazurowski, William Paul Segars, Ehsan Samei, Joseph Y. Lo:
Virtual vs. Reality: External Validation of COVID-19 Classifiers using XCAT Phantoms for Chest Computed Tomography. CoRR abs/2203.03074 (2022) - [i19]Hanxue Gu, Keyu Li, Roy J. Colglazier, Jichen Yang, Michael Lebhar, Jonathan O'Donnell, William A. Jiranek, Richard C. Mather, Rob J. French, Nicholas Said, Jikai Zhang, Christine Park, Maciej A. Mazurowski:
Automated Grading of Radiographic Knee Osteoarthritis Severity Combined with Joint Space Narrowing. CoRR abs/2203.08914 (2022) - [i18]Jikai Zhang, Maciej A. Mazurowski, Brian C. Allen, Benjamin Wildman-Tobriner:
Multistep Automated Data Labelling Procedure (MADLaP) for Thyroid Nodules on Ultrasound: An Artificial Intelligence Approach for Automating Image Annotation. CoRR abs/2206.14305 (2022) - [i17]Nicholas Konz, Hanxue Gu, Haoyu Dong, Maciej A. Mazurowski:
The Intrinsic Manifolds of Radiological Images and their Role in Deep Learning. CoRR abs/2207.02797 (2022) - [i16]Albert Swiecicki, Nianyi Li, Jonathan O'Donnell, Nicholas Said, Jichen Yang, Richard C. Mather, William A. Jiranek, Maciej A. Mazurowski:
Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists. CoRR abs/2207.12521 (2022) - [i15]Jingxi Weng, Benjamin Wildman-Tobriner, Mateusz Buda, Jichen Yang, Lisa M. Ho, Brian C. Allen, Wendy L. Ehieli, Chad M. Miller, Jikai Zhang, Maciej A. Mazurowski:
Deep Learning for Classification of Thyroid Nodules on Ultrasound: Validation on an Independent Dataset. CoRR abs/2207.13765 (2022) - 2021
- [i14]Vincent M. D'Anniballe, Fakrul Islam Tushar, Khrystyna Faryna, Songyue Han, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo:
Multi-Label Annotation of Chest Abdomen Pelvis Computed Tomography Text Reports Using Deep Learning. CoRR abs/2102.02959 (2021) - [i13]Maciej A. Mazurowski:
Do We Expect More from Radiology AI than from Radiologists? CoRR abs/2105.06264 (2021) - [i12]Yifan Zhang, Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej A. Mazurowski:
REPLICA: Enhanced Feature Pyramid Network by Local Image Translation and Conjunct Attention for High-Resolution Breast Tumor Detection. CoRR abs/2111.11546 (2021) - 2020
- [i11]Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin:
Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes. CoRR abs/2002.04752 (2020) - [i10]Fakrul Islam Tushar, Vincent M. D'Anniballe, Rui Hou, Maciej A. Mazurowski, Wanyi Fu, Ehsan Samei, Geoffrey D. Rubin, Joseph Y. Lo:
Weakly Supervised Multi-Organ Multi-Disease Classification of Body CT Scans. CoRR abs/2008.01158 (2020) - [i9]Anindo Saha, Fakrul Islam Tushar, Khrystyna Faryna, Vincent M. D'Anniballe, Rui Hou, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo:
Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features. CoRR abs/2011.00149 (2020) - [i8]Mateusz Buda, Ashirbani Saha, Ruth Walsh, Sujata V. Ghate, Nianyi Li, Albert Swiecicki, Joseph Y. Lo, Maciej A. Mazurowski:
Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5, 060 patients and a deep learning model. CoRR abs/2011.07995 (2020) - 2019
- [i7]Mateusz Buda, Ashirbani Saha, Maciej A. Mazurowski:
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm. CoRR abs/1906.03720 (2019) - [i6]Gourav Modanwal, Adithya Vellal, Maciej A. Mazurowski:
Normalization of breast MRIs using Cycle-Consistent Generative Adversarial Networks. CoRR abs/1912.08061 (2019) - 2018
- [i5]Maciej A. Mazurowski, Mateusz Buda, Ashirbani Saha, Mustafa R. Bashir:
Deep learning in radiology: an overview of the concepts and a survey of the state of the art. CoRR abs/1802.08717 (2018) - [i4]Jun Zhang, Ashirbani Saha, Brian J. Soher, Maciej A. Mazurowski:
Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images. CoRR abs/1807.02152 (2018) - 2017
- [i3]Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski:
A systematic study of the class imbalance problem in convolutional neural networks. CoRR abs/1710.05381 (2017) - [i2]Zhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, Eun-Sil Shelley Hwang, Maciej A. Mazurowski:
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ. CoRR abs/1711.10577 (2017) - [i1]Zhe Zhu, Ehab Albadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski:
Deep Learning for identifying radiogenomic associations in breast cancer. CoRR abs/1711.11097 (2017)
Coauthor Index
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