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Aria Pezeshk
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2020 – today
- 2023
- [c13]Molly O'Brien, Brett Wolfinger, Julia V. Bukowski
, Mathias Unberath, Aria Pezeshk, Greg Hager:
Mapping DNN Embedding Manifolds for Network Generalization Prediction. WACV 2023: 6513-6522 - 2022
- [c12]Molly O'Brien, Julia V. Bukowski
Evaluating neural network robustness for melanoma classification using mutual information. Image Processing 2022 - [i1]Molly O'Brien, Julia V. Bukowski, Mathias Unberath, Aria Pezeshk, Greg Hager:
Mapping DNN Embedding Manifolds for Network Generalization Prediction. CoRR abs/2202.03868 (2022) - 2021
- [j5]Alexej Gossmann, Aria Pezeshk, Yu-Ping Wang, Berkman Sahiner:
Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve. SIAM J. Math. Data Sci. 3(2): 692-714 (2021) - 2020
- [c11]Benjamin Veasey, Mohammad Mehdi Farhangi, Hichem Frigui, Justin Broadhead, Michael Dahle, Aria Pezeshk, Albert Seow, Amir A. Amini:
Lung Nodule Malignancy Classification Based ON NLSTx Data. ISBI 2020: 1870-1874
2010 – 2019
- 2019
- [j4]Aria Pezeshk
3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT. IEEE J. Biomed. Health Informatics 23(5): 2080-2090 (2019) - [c10]Kenny H. Cha, Nicholas Petrick, Aria Pezeshk, Christian G. Graff
Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images. Computer-Aided Diagnosis 2019: 1095004 - 2018
- [c9]Zahra Ghanian, Aria Pezeshk, Nicholas Petrick, Berkman Sahiner:
Towards the use of computationally inserted lesions for mammographic CAD assessment. Image Perception, Observer Performance, and Technology Assessment 2018: 105770L - [c8]Alexej Gossmann
Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed 'test' dataset and a potential solution. Image Perception, Observer Performance, and Technology Assessment 2018: 105770K - [c7]Jiheng Wang, Berkman Sahiner, Nicholas Petrick, Aria Pezeshk:
A database for assessment of effect of lossy compression on digital mammograms. Image Perception, Observer Performance, and Technology Assessment 2018: 1057706 - 2017
- [j3]Aria Pezeshk
Seamless Lesion Insertion for Data Augmentation in CAD Training. IEEE Trans. Medical Imaging 36(4): 1005-1015 (2017) - [c6]Sardar Hamidian, Berkman Sahiner, Nicholas Petrick, Aria Pezeshk:
3D convolutional neural network for automatic detection of lung nodules in chest CT. Computer-Aided Diagnosis 2017: 1013409 - 2016
- [c5]Aria Pezeshk, Nicholas Petrick, Berkman Sahiner:
Seamless lesion insertion in digital mammography: methodology and reader study. Computer-Aided Diagnosis 2016: 97850J - [c4]Berkman Sahiner, Weijie Chen, Aria Pezeshk, Nicholas Petrick:
Semi-parametric estimation of the area under the precision-recall curve. Image Perception, Observer Performance, and Technology Assessment 2016: 97870D - 2015
- [j2]Aria Pezeshk
Seamless Insertion of Pulmonary Nodules in Chest CT Images. IEEE Trans. Biomed. Eng. 62(12): 2812-2827 (2015) - [c3]Aria Pezeshk, Berkman Sahiner, Weijie Chen, Nicholas Petrick:
Improving CAD performance by seamless insertion of pulmonary nodules in chest CT exams. Computer-Aided Diagnosis 2015: 94140A - 2014
- [c2]Aria Pezeshk, Berkman Sahiner, Rongping Zeng, Adam Wunderlich, Weijie Chen, Nicholas Petrick:
Seamless insertion of real pulmonary nodules in chest CT exams. Computer-Aided Diagnosis 2014: 90351K - 2011
- [j1]Aria Pezeshk, Richard L. Tutwiler:
Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps. IEEE Trans. Geosci. Remote. Sens. 49(12): 5047-5063 (2011) - 2010
- [c1]Aria Pezeshk, Richard L. Tutwiler:
Improved Multi Angled Parallelism for separation of text from intersecting linear features in scanned topographic maps. ICASSP 2010: 1078-1081
Coauthor Index
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