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AJR. American Journal of Roentgenology
|
November 21, 2015
The Use of Lossy Compression of Digital Mammograms for Primary Interpretation and Image Retention
David L Lerner, Aria Pezeshk
Proceedings of Spie--The International Society for Optical Engineering
|
August 29, 2017
3D Convolutional Neural Network for Automatic Detection of Lung Nodules in Chest CT
Sardar Hamidian, Berkman Sahiner, Nicholas Petrick, et al.
IEEE Journal of Biomedical and Health Informatics
|
November 13, 2018
3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT
Aria Pezeshk, Sardar Hamidian, Nicholas Petrick, et al.
IEEE Transactions on Medical Imaging
|
January 24, 2017
Seamless Lesion Insertion for Data Augmentation in CAD Training
Aria Pezeshk, Nicholas Petrick, Weijie Chen, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
March 7, 2019
Computational insertion of microcalcification clusters on mammograms: reader differentiation from native clusters and computer-aided detection comparison
Zahra Ghanian, Aria Pezeshk, Nicholas Petrick, et al.
Medical Physics
|
May 1, 2021
Automatic lung nodule detection in thoracic CT scans using dilated slice-wise convolutions
M Mehdi Farhangi, Berkman Sahiner, Nicholas Petrick, et al.
Statistical Methods in Medical Research
|
August 11, 2016
Calibration of medical diagnostic classifier scores to the probability of disease
Weijie Chen, Berkman Sahiner, Frank Samuelson, et al.
IEEE Transactions on Bio-Medical Engineering
|
June 17, 2015
Seamless Insertion of Pulmonary Nodules in Chest CT Images
Aria Pezeshk, Berkman Sahiner, Rongping Zeng, et al.
Medical Physics
|
February 8, 2020
Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans
M Mehdi Farhangi, Nicholas Petrick, Berkman Sahiner, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
November 26, 2019
Evaluation of data augmentation via synthetic images for improved breast mass detection on mammograms using deep learning
Kenny H Cha, Nicholas Petrick, Aria Pezeshk, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 14) with videos related to
Sort By:
Page
of 2
AJR. American Journal of Roentgenology
|
November 21, 2015
The Use of Lossy Compression of Digital Mammograms for Primary Interpretation and Image Retention
David L Lerner, Aria Pezeshk
Proceedings of Spie--The International Society for Optical Engineering
|
August 29, 2017
3D Convolutional Neural Network for Automatic Detection of Lung Nodules in Chest CT
Sardar Hamidian, Berkman Sahiner, Nicholas Petrick, et al.
IEEE Journal of Biomedical and Health Informatics
|
November 13, 2018
3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT
Aria Pezeshk, Sardar Hamidian, Nicholas Petrick, et al.
IEEE Transactions on Medical Imaging
|
January 24, 2017
Seamless Lesion Insertion for Data Augmentation in CAD Training
Aria Pezeshk, Nicholas Petrick, Weijie Chen, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
March 7, 2019
Computational insertion of microcalcification clusters on mammograms: reader differentiation from native clusters and computer-aided detection comparison
Zahra Ghanian, Aria Pezeshk, Nicholas Petrick, et al.
Medical Physics
|
May 1, 2021
Automatic lung nodule detection in thoracic CT scans using dilated slice-wise convolutions
M Mehdi Farhangi, Berkman Sahiner, Nicholas Petrick, et al.
Statistical Methods in Medical Research
|
August 11, 2016
Calibration of medical diagnostic classifier scores to the probability of disease
Weijie Chen, Berkman Sahiner, Frank Samuelson, et al.
IEEE Transactions on Bio-Medical Engineering
|
June 17, 2015
Seamless Insertion of Pulmonary Nodules in Chest CT Images
Aria Pezeshk, Berkman Sahiner, Rongping Zeng, et al.
Medical Physics
|
February 8, 2020
Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans
M Mehdi Farhangi, Nicholas Petrick, Berkman Sahiner, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
November 26, 2019
Evaluation of data augmentation via synthetic images for improved breast mass detection on mammograms using deep learning
Kenny H Cha, Nicholas Petrick, Aria Pezeshk, et al.
Page
of 2