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Aria Pezeshk
Aria Pezeshk
Unknown affiliation
Verified email at fda.hhs.gov
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Cited by
Year
Deep learning in medical imaging and radiation therapy
B Sahiner, A Pezeshk, LM Hadjiiski, X Wang, K Drukker, KH Cha, ...
Medical physics 46 (1), e1-e36, 2019
7472019
3D convolutional neural network for automatic detection of lung nodules in chest CT
S Hamidian, B Sahiner, N Petrick, A Pezeshk
Medical Imaging 2017: Computer-Aided Diagnosis 10134, 54-59, 2017
1452017
3-D convolutional neural networks for automatic detection of pulmonary nodules in chest CT
A Pezeshk, S Hamidian, N Petrick, B Sahiner
IEEE journal of biomedical and health informatics 23 (5), 2080-2090, 2018
1002018
Automatic feature extraction and text recognition from scanned topographic maps
A Pezeshk, RL Tutwiler
IEEE Transactions on Geoscience and Remote Sensing 49 (12), 5047-5063, 2011
1002011
Seamless lesion insertion for data augmentation in CAD training
A Pezeshk, N Petrick, W Chen, B Sahiner
IEEE transactions on medical imaging 36 (4), 1005-1015, 2016
462016
Evaluation of data augmentation via synthetic images for improved breast mass detection on mammograms using deep learning
KH Cha, N Petrick, A Pezeshk, CG Graff, D Sharma, A Badal, B Sahiner
Journal of Medical Imaging 7 (1), 012703-012703, 2020
392020
Calibration of medical diagnostic classifier scores to the probability of disease
W Chen, B Sahiner, F Samuelson, A Pezeshk, N Petrick
Statistical methods in medical research 27 (5), 1394-1409, 2018
272018
Contour line recognition & extraction from scanned colour maps using dual quantization of the intensity image
A Pezeshk, RL Tutwiler
2008 IEEE Southwest Symposium on Image Analysis and Interpretation, 173-176, 2008
242008
Seamless insertion of pulmonary nodules in chest CT images
A Pezeshk, B Sahiner, R Zeng, A Wunderlich, W Chen, N Petrick
IEEE Transactions on Biomedical Engineering 62 (12), 2812-2827, 2015
222015
Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans
MM Farhangi, N Petrick, B Sahiner, H Frigui, AA Amini, A Pezeshk
Medical physics 47 (5), 2150-2160, 2020
202020
Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT
M Robins, J Solomon, P Sahbaee, M Sedlmair, KR Choudhury, ...
Physics in Medicine & Biology 62 (18), 7280, 2017
182017
Improved multi angled parallelism for separation of text from intersecting linear features in scanned topographic maps
A Pezeshk, RL Tutwiler
2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010
172010
Comparison of two classifiers when the data sets are imbalanced: the power of the area under the precision-recall curve as the figure of merit versus the area under the ROC curve
B Sahiner, W Chen, A Pezeshk, N Petrick
Medical Imaging 2017: Image Perception, Observer Performance, and Technology …, 2017
162017
Lung nodule malignancy classification based on NLSTx Data
B Veasey, MM Farhangi, H Frigui, J Broadhead, M Dahle, A Pezeshk, ...
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1870-1874, 2020
152020
Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images
KH Cha, N Petrick, A Pezeshk, CG Graff, D Sharma, A Badal, A Badano, ...
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 13-19, 2019
152019
Extended character defect model for recognition of text from maps
A Pezeshk, RL Tutwiler
2010 IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI), 85-88, 2010
152010
Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed'test'dataset and a potential solution
A Gossmann, A Pezeshk, B Sahiner
Medical Imaging 2018: Image Perception, Observer Performance, and Technology …, 2018
122018
Automatic lung nodule detection in thoracic CT scans using dilated slice-wise convolutions
MM Farhangi, B Sahiner, N Petrick, A Pezeshk
Medical Physics 48 (7), 3741-3751, 2021
102021
Test data reuse for the evaluation of continuously evolving classification algorithms using the area under the receiver operating characteristic curve
A Gossmann, A Pezeshk, YP Wang, B Sahiner
SIAM Journal on Mathematics of Data Science 3 (2), 692-714, 2021
102021
Evaluation of simulated lesions as surrogates to clinical lesions for thoracic CT volumetry: the results of an international challenge
M Robins, J Kalpathy-Cramer, NA Obuchowski, A Buckler, M Athelogou, ...
Academic radiology 26 (7), e161-e173, 2019
72019
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