Effect of viewing angle on visual detection in liquid crystal displays. - Aldo Badano; Brandon D. Gallas; Kyle J. Myers; Arthur E. Burgess (Image-Guided Procedures, 2003)

Visual detection with non-Lambertian displays: model and human observer results. - Aldo Badano; Brandon D. Gallas; Dipesh H. Fifadara (Image-Guided Procedures, 2005)

Framework for determination of geometric parameters of a cone beam CT scanner for measuring the system response function and improved object reconstruction. - Iacovos S. Kyprianou; Sophie Paquerault; Brandon D. Gallas; Aldo Badano; Subok Park; Kyle J. Myers (ISBI, 2006)

Leveraging the Digital Mammography Image Screening Trial (DMIST) Data for the Evaluation of Computer-Aided Detection (CAD) Devices: A Proposal. - Nicholas Petrick; Kyle J. Myers; Sophie Paquerault; Frank W. Samuelson; Brandon D. Gallas; Robert F. Wagner (Digital Mammography / IWDM, 2006)

Performance Studies for Validation of CAD Systems. - David G. Brown; Brandon D. Gallas (IJCNN, 2007)

Methods for MRMC Roc Analysis and Components-Ofvariance Modeling Using Colposcopy Images. - Elizabeth R. Hsu; Brandon D. Gallas; Jose Jeronimo (ISBI, 2007)

Reader studies for validation of CAD systems. - Brandon D. Gallas; David G. Brown (Neural Networks, 2008)

Incorporating Human Contrast Sensitivity in Model Observers for Detection Tasks. - Subok Park; Aldo Badano; Brandon D. Gallas; Kyle J. Myers (IEEE Trans. Medical Imaging, 2009)

Training variability in the evaluation of automated classifiers. - Weijie Chen 007; Brandon D. Gallas (Computer-Aided Diagnosis, 2010)

Three-Class ROC Analysis - Toward a General Decision Theoretic Solution. - Xin He; Brandon D. Gallas; Eric C. Frey (IEEE Trans. Medical Imaging, 2010)

Uncertainty estimation with a finite dataset in the assessment of classification models. - Weijie Chen 007; Waleed A. Yousef; Brandon D. Gallas; Elizabeth R. Hsu; Samir Lababidi; Rong Tang; Gene A. Pennello; W. Fraser Symmans; Lajos Pusztai (Comput. Stat. Data Anal., 2012)

Classifier variability: Accounting for training and testing. - Weijie Chen 007; Brandon D. Gallas; Waleed A. Yousef (Pattern Recognit., 2012)

Assessing color reproducibility of whole-slide imaging scanners. - Wei-Chung Cheng; Tyler Keay; Neil O'Flaherty; Joel Wang; Adam Ivansky; Marios A. Gavrielides; Brandon D. Gallas; Aldo Badano (Digital Pathology, 2013)

Uncertainty in the assessment of immunohistochemical staining with optical and digital microscopy: lessons from a reader study. - Marios A. Gavrielides; Brandon D. Gallas; Stephen M. Hewitt (Digital Pathology, 2015)

Exact Confidence Intervals for Channelized Hotelling Observer Performance in Image Quality Studies. - Adam Wunderlich; Frédéric Noo; Brandon D. Gallas; Marta E. Heilbrun (IEEE Trans. Medical Imaging, 2015)

MRMC analysis of agreement studies. - Brandon D. Gallas; Amrita Anam; Weijie Chen 007; Adam Wunderlich; Zhiwei Zhang (Image Perception, Observer Performance, and Technology Assessment, 2016)

Registration accuracy between whole slide images and glass slides in eeDAP workflow. - Qi Gong; Benjamin P. Berman; Marios A. Gavrielides; Brandon D. Gallas (Digital Pathology, 2018)

Efficiency gain of paired split-plot designs in MRMC ROC studies. - Weijie Chen 007; Qi Gong; Brandon D. Gallas (Image Perception, Observer Performance, and Technology Assessment, 2018)

FDA fosters innovative approaches in research, resources and collaboration. - Brandon D. Gallas; Aldo Badano; Sarah Dudgeon; Katherine Elfer; Victor Garcia; Jochen K. Lennerz; Kyle J. Myers; Nicholas Petrick; Ed Margerrison (Nat. Mach. Intell., 2022)

Effect of color-normalization on deep learning segmentation models for tumor-infiltrating lymphocytes scoring using breast cancer histopathology images. - Arian Arab; Victor Garcia; Shuyue Guan 001; Brandon D. Gallas; Berkman Sahiner; Nicholas Petrick; Weijie Chen 007 (Digital and Computational Pathology, 2023)

Analysis of a pilot study collecting pathologist annotations for validating machine learning algorithms. - Katherine Elfer; Victor Garcia; Brandon D. Gallas (Image Perception, Observer Performance, and Technology Assessment, 2023)