Improved Multi Angled Parallelism for separation of text from intersecting linear features in scanned topographic maps. - Aria Pezeshk; Richard L. Tutwiler (ICASSP, 2010)

Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps. - Aria Pezeshk; Richard L. Tutwiler (IEEE Trans. Geosci. Remote. Sens., 2011)

Seamless insertion of real pulmonary nodules in chest CT exams. - Aria Pezeshk; Berkman Sahiner; Rongping Zeng; Adam Wunderlich; Weijie Chen 007; Nicholas Petrick (Computer-Aided Diagnosis, 2014)

Improving CAD performance by seamless insertion of pulmonary nodules in chest CT exams. - Aria Pezeshk; Berkman Sahiner; Weijie Chen 007; Nicholas Petrick (Computer-Aided Diagnosis, 2015)

Seamless Insertion of Pulmonary Nodules in Chest CT Images. - Aria Pezeshk; Berkman Sahiner; Rongping Zeng; Adam Wunderlich; Weijie Chen 007; Nicholas Petrick (IEEE Trans. Biomed. Eng., 2015)

Seamless lesion insertion in digital mammography: methodology and reader study. - Aria Pezeshk; Nicholas Petrick; Berkman Sahiner (Computer-Aided Diagnosis, 2016)

Semi-parametric estimation of the area under the precision-recall curve. - Berkman Sahiner; Weijie Chen 007; Aria Pezeshk; Nicholas Petrick (Image Perception, Observer Performance, and Technology Assessment, 2016)

3D convolutional neural network for automatic detection of lung nodules in chest CT. - Sardar Hamidian; Berkman Sahiner; Nicholas Petrick; Aria Pezeshk (Computer-Aided Diagnosis, 2017)

Seamless Lesion Insertion for Data Augmentation in CAD Training. - Aria Pezeshk; Nicholas Petrick; Weijie Chen 007; Berkman Sahiner (IEEE Trans. Medical Imaging, 2017)

Towards the use of computationally inserted lesions for mammographic CAD assessment. - Zahra Ghanian; Aria Pezeshk; Nicholas Petrick; Berkman Sahiner (Image Perception, Observer Performance, and Technology Assessment, 2018)

Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed 'test' dataset and a potential solution. - Alexej Gossmann; Aria Pezeshk; Berkman Sahiner (Image Perception, Observer Performance, and Technology Assessment, 2018)

A database for assessment of effect of lossy compression on digital mammograms. - Jiheng Wang; Berkman Sahiner; Nicholas Petrick; Aria Pezeshk (Image Perception, Observer Performance, and Technology Assessment, 2018)

Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images. - Kenny H. Cha; Nicholas Petrick; Aria Pezeshk; Christian G. Graff; Diksha Sharma; Andreu Badal; Aldo Badano; Berkman Sahiner (Computer-Aided Diagnosis, 2019)

3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT. - Aria Pezeshk; Sardar Hamidian; Nicholas Petrick; Berkman Sahiner (IEEE J. Biomed. Health Informatics, 2019)

Lung Nodule Malignancy Classification Based ON NLSTx Data. - Benjamin Veasey; Mohammad Mehdi Farhangi; Hichem Frigui; Justin Broadhead; Michael Dahle; Aria Pezeshk; Albert Seow; Amir A. Amini (ISBI, 2020)

Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve. - Alexej Gossmann; Aria Pezeshk; Yu-Ping Wang 002; Berkman Sahiner (SIAM J. Math. Data Sci., 2021)

Evaluating neural network robustness for melanoma classification using mutual information. - Molly O'Brien; Julia V. Bukowski; Greg Hager; Aria Pezeshk; Mathias Unberath (Image Processing, 2022)

Mapping DNN Embedding Manifolds for Network Generalization Prediction. - Molly O'Brien; Julia V. Bukowski; Mathias Unberath; Aria Pezeshk; Greg Hager (CoRR, 2022)

Mapping DNN Embedding Manifolds for Network Generalization Prediction. - Molly O'Brien; Brett Wolfinger; Julia V. Bukowski; Mathias Unberath; Aria Pezeshk; Greg Hager (WACV, 2023)