Maciej A. Mazurowski

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 91

Top Venues

CoRR

Medical Imaging: Computer-Aided Diagnosis

Comput. Biol. Medicine

Expert Syst. Appl.

Publications

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 (2024)
Nicholas Konz, Maciej A. Mazurowski
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images. CoRR (2024)
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 (2024)
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 (2024)
Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej A. Mazurowski
Medical Image Segmentation with InTEnt: Integrated Entropy Weighting for Single Image Test-Time Adaptation. CoRR (2024)
Nicholas Konz, Maciej A. Mazurowski
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images. ICLR (2024)
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 (2024)
Nicholas Konz, Yuwen Chen, Haoyu Dong, Maciej A. Mazurowski
Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models. CoRR (2024)
Yixin Zhang, Maciej A. Mazurowski
Convolutional neural networks rarely learn shape for semantic segmentation. Pattern Recognit. 146 (2024)
Nicholas Konz, Yuwen Chen, Hanxue Gu, Haoyu Dong, Maciej A. Mazurowski
Rethinking Perceptual Metrics for Medical Image Translation. CoRR (2024)
Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, Yixin Zhang
Segment Anything Model for Medical Image Analysis: an Experimental Study. CoRR (2023)
Nicholas Konz, Haoyu Dong, Maciej A. Mazurowski
Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion. Medical Image Anal. 87 (2023)
Nicholas Konz, Maciej A. Mazurowski
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images. CoRR (2023)
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)
Yixin Zhang, Maciej A. Mazurowski
Convolutional Neural Networks Rarely Learn Shape for Semantic Segmentation. CoRR (2023)
Jee Seok Yoon, Kwanseok Oh, Yooseung Shin, Maciej A. Mazurowski, Heung-Il Suk
Domain Generalization for Medical Image Analysis: A Survey. CoRR (2023)
Jikai Zhang, Carlos Santos, Christine Park, Maciej A. Mazurowski, Roy J. Colglazier
Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach. CoRR (2023)
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 (2023)
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 (2023)
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) (2023)
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 (2023)
Nicholas Konz, Maciej A. Mazurowski
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images. MIDL (2023)
Shixing Cao, Nicholas Konz, James Duncan, Maciej A. Mazurowski
Deep Learning for Breast MRI Style Transfer with Limited Training Data. CoRR (2023)
Nicholas Konz, Haoyu Dong, Maciej A. Mazurowski
Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion. CoRR (2023)
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 (2023)
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) (2023)
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 (2023)
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) (2023)
Nicholas Konz, Hanxue Gu, Haoyu Dong, Maciej A. Mazurowski
The Intrinsic Manifolds of Radiological Images and their Role in Deep Learning. CoRR (2022)
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) (2022)
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 (2022)
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)
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) (2022)
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 (2022)
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) (2022)
Yifan Zhang, Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej A. Mazurowski
Lightweight Transformer Backbone for Medical Object Detection. CaPTion@MICCAI (2022)
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 (2022)
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 (2022)
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 (2022)
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 (2022)
Nicholas Konz, Hanxue Gu, Haoyu Dong, Maciej A. Mazurowski
The Intrinsic Manifolds of Radiological Images and Their Role in Deep Learning. MICCAI (8) (2022)
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 (2021)
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)
Gourav Modanwal, Adithya Vellal, Maciej A. Mazurowski
Normalization of breast MRIs using cycle-consistent generative adversarial networks. Comput. Methods Programs Biomed. 208 (2021)
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 (2021)
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 (2021)
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 (2021)
Maciej A. Mazurowski
Do We Expect More from Radiology AI than from Radiologists? CoRR (2021)
Gourav Modanwal, Adithya Vellal, Mateusz Buda, Maciej A. Mazurowski
MRI image harmonization using cycle-consistent generative adversarial network. Medical Imaging: Computer-Aided Diagnosis (2020)
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)
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)
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 (2020)
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)
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 (2020)
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 (2020)
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)
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) (2020)
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 (2020)
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)
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)
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 (2019)
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 (2019)
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)
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 (2019)
Gourav Modanwal, Adithya Vellal, Maciej A. Mazurowski
Normalization of breast MRIs using Cycle-Consistent Generative Adversarial Networks. CoRR (2019)
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) (2019)
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)
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)
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)
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)
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 (2018)
Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski
A systematic study of the class imbalance problem in convolutional neural networks. Neural Networks 106 (2018)
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)
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)
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)
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)
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)
Jun Zhang, Ashirbani Saha, Brian J. Soher, Maciej A. Mazurowski
Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images. CoRR (2018)
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)
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)
Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski
A systematic study of the class imbalance problem in convolutional neural networks. CoRR (2017)
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)
Ashirbani Saha, Xiaozhi Yu, Dushyant Sahoo, Maciej A. Mazurowski
Effects of MRI scanner parameters on breast cancer radiomics. Expert Syst. Appl. 87 (2017)
Zhe Zhu, Ehab Albadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski
Deep Learning for identifying radiogenomic associations in breast cancer. CoRR (2017)
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)
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 (2017)
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)
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 (2016)
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)
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 (2016)
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)
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 (2015)
Maciej A. Mazurowski
Estimating confidence of individual rating predictions in collaborative filtering recommender systems. Expert Syst. Appl. 40 (10) (2013)
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 (2012)
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) (2011)
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)
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)
Maciej A. Mazurowski, Georgia D. Tourassi
Evaluating classifiers: Relation between area under the receiver operator characteristic curve and overall accuracy. IJCNN (2009)
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)
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)

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Publication Activity (10 Years)

Top Topics

Top Venues

Maciej A. Mazurowski