Michael F. McNitt-Gray

发表

Solitary pulmonary nodule characterization on CT by use of contrast enhancement maps

Sumit K. Shah, Michael F. McNitt-Gray, Iva Petkovska, 2005, SPIE Medical Imaging.

Michael F. McNitt-Gray, Ricky K. Taira, Claudine M. Breant, 1992 .

The Lung Image Database Consortium (LIDC): pulmonary nodule measurements, the variation, and the difference between different size metrics

Geoffrey McLennan, Eric A. Hoffman, Michael F. McNitt-Gray, 2007, SPIE Medical Imaging.

Effect of Edge-Preserving Adaptive Image Filter on Low-Contrast Detectability in CT Systems: Application of ROC Analysis

Michael F. McNitt-Gray, Miwa Okumura, Takamasa Ota, 2008, Int. J. Biomed. Imaging.

An automatic method for enhancing the display of different tissue densities in digital chest radiographs

Michael F. McNitt-Gray, Ricky K. Taira, Sandy L. Johnson, 2009, Journal of Digital Imaging.

Automatic segmentation of lung parenchyma based on curvature of ribs using HRCT images in scleroderma studies

Michael F. McNitt-Gray, Jonathan G. Goldin, M. N. Prasad, 2008, SPIE Medical Imaging.

Knowledge-based segmentation of pediatric kidneys in CT for measuring parenchymal volume

Michael F. McNitt-Gray, Matthew S. Brown, Waldo C. Feng, 2000, Medical Imaging: Image Processing.

An extensible knowledge-based architecture for segmenting computed tomography images

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1997, Proceedings of International Conference on Image Processing.

CT Assessment of Response to Therapy: Tumor Volume Change Measurement, Truth Data & Error | NIST

Geoffrey McLennan, Marios A. Gavrielides, Nicholas Petrick, 2009 .

The relationship between organ dose and patient size in tube current modulated adult thoracic CT scans

Michael F. McNitt-Gray, Di Zhang, Maryam Khatonabadi, 2012, Medical Imaging.

Method for segmenting chest CT image data using an anatomical model: preliminary results

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1997, IEEE Transactions on Medical Imaging.

Database design and implementation for quantitative image analysis research

Sumit K. Shah, Michael F. McNitt-Gray, Jonathan G. Goldin, 2005, IEEE Transactions on Information Technology in Biomedicine.

Lung nodules and beyond: approaches, challenges and opportunities in thoracic CAD

Michael F. McNitt-Gray, 2004, CARS.

TH‐E‐217BCD‐08: Simulating Reduced‐Dose CT Imaging Using an Image‐Based Virtual Sinogram Approach: Comparisons with Real Sinogram‐Based Simulation

Michael F. McNitt-Gray, C Kim, C Kim, 2012 .

Techniques for multiple-signal multiple-reader evaluations

Michael F. McNitt-Gray, H. K. Huang, Brent K. Stewart, 1993 .

Separation of bone from iodine- and gadolinium-based contrast agents using dual energy CT

Michael F. McNitt-Gray, Jonathan G. Goldin, Daniel Y. Chong, 2008, SPIE Medical Imaging.

Evaluation of 1D, 2D and 3D nodule size estimation by radiologists for spherical and non-spherical nodules through CT thoracic phantom imaging

Marios A. Gavrielides, Rongping Zeng, Michael F. McNitt-Gray, 2011, Medical Imaging.

Computerized bone analysis of hand radiographs

Michael F. McNitt-Gray, Ewa Pietka, Theodore R. Hall, 1992, Medical Imaging.

Estimating lesion volume in low-dose chest CT: How low can we go?

Michael F. McNitt-Gray, Stefano Young, M. McNitt-Gray, 2014, Medical Imaging.

Forming a reference standard from LIDC data: impact of reader agreement on reported CAD performance

Michael F. McNitt-Gray, Matthew S. Brown, Hyun J. Kim, 2007, SPIE Medical Imaging.

[P180] Records: Guidelines for publication of monte carlo studies

Michael F. McNitt-Gray, Wesley E. Bolch, Ioannis Sechopoulos, 2018 .

The evolution of an integrated timeline for oncology patient healthcare

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1998, AMIA.

Contrast enhancement maps for lung lesions imaged on CT

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 2000, Medical Imaging.

Towards quantitative imaging: stability of fully automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose CT screening patient cohort

Michael F. McNitt-Gray, Matthew S. Brown, John M. Hoffman, 2018, Medical Imaging.

Monte-Carlo-based simulation tool to model the physics and geometry of electron beam computed tomography

Michael F. McNitt-Gray, John J. DeMarco, Chris H. Cagnon, 2001, SPIE Medical Imaging.

Robustness-Driven Feature Selection in Classification of Fibrotic Interstitial Lung Disease Patterns in Computed Tomography Using 3D Texture Features

Michael F. McNitt-Gray, Jonathan G. Goldin, Matthew S. Brown, 2016, IEEE Transactions on Medical Imaging.

TimeLine: A Multimedia, Problem-Centric Visualization of Patient Records

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1999, AMIA.

The Lung Image Database Consortium (LIDC): a quality assurance model for the collection of expert-defined truth in lung-nodule-based image analysis studies

Eric A. Hoffman, Michael F. McNitt-Gray, Denise R. Aberle, 2007, SPIE Medical Imaging.

Assessing nodule detection on lung cancer screening CT: the effects of tube current modulation and model observer selection on detectability maps

Michael F. McNitt-Gray, S. Young, Frédéric Noo, 2016, SPIE Medical Imaging.

Tracking Veteran Patient's Organ Dose from Abdominal CT Exams

Michael F. McNitt-Gray, Craig A. Morioka, Adam Turner, 2012, AMIA.

Reconstruction algorithm effects on density mask score and volume in patients with low amounts of emphysema

Michael F. McNitt-Gray, Jonathan G. Goldin, Matthew S. Brown, 2003, SPIE Medical Imaging.

Object-oriented region-of-interest toolkit for workstations

Michael F. McNitt-Gray, Matthew S. Brown, Nathaniel Wyckoff, 1998, Medical Imaging.

Effects of CT dose and nodule characteristics on lung-nodule detectability in a cohort of 90 national lung screening trial patients

Michael F. McNitt-Gray, Matthew S. Brown, Pechin Lo, 2016, SPIE Medical Imaging.

Tradeoffs in noise, resolution, and dose with reconstruction filter selection in lung nodule detection in CT

Michael F. McNitt-Gray, Kirsten L. Boedeker, M. McNitt-Gray, 2005, SPIE Medical Imaging.

The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation

Michael F. McNitt-Gray, Denise R. Aberle, Heber MacMahon, 2007, SPIE Medical Imaging.

Determining the Variability of Lesion Size Measurements from CT Patient Data Sets Acquired under “No Change” Conditions12

Michael F. McNitt-Gray, Nicholas Petrick, Lawrence H. Schwartz, 2015, Translational oncology.

Pattern classification approach to segmentation of digital chest radiographs and chest CT image slices

H. K. Huang, Michael F. McNitt-Gray, Denise R. Aberle, 1994, Medical Imaging.

The accuracy of estimated organ doses from Monte Carlo CT simulations using cylindrical regions of interest within organs

John J. DeMarco, Michael F. McNitt-Gray, Di Zhang, 2011, Medical Imaging.

A model-guided feedback control system for image segmentation

Michael F. McNitt-Gray, Alfonso F. Cardenas, Hyeonjoon Shim, 1999 .

Effect of pitch, collimation, and reconstruction interval on low-contrast detectability in spiral computed tomography

Michael F. McNitt-Gray, Keyvan Farahani, Carolyn Kimme-Smith, 1999, Medical Imaging.

Classification of solitary pulmonary nodules (SPNs) imaged on high-resolution CT using contrast enhancement and three-dimensional quantitative image features

Michael F. McNitt-Gray, Jonathan G. Goldin, Robert D. Suh, 2000, Medical Imaging: Image Processing.

The influence of CT dose and reconstruction parameters on automated detection of small pulmonary nodules

Michael F. McNitt-Gray, Iva Petkovska, Jonathan G. Goldin, 2006, SPIE Medical Imaging.

Application of Information Technology: Problem-oriented Prefetching for an Integrated Clinical Imaging Workstation

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 2001, J. Am. Medical Informatics Assoc..

Computed radiography dual energy subtraction: Performance evaluation when detecting low-contrast lung nodules in an anthropomorphic phantom

Michael F. McNitt-Gray, Jonathan G. Goldin, Timothy D. Johnson, 2009, Journal of Digital Imaging.

Differentiating solitary pulmonary nodules (SPNs) with 3D shape features

Yang Wang, Michael F. McNitt-Gray, Jonathan G. Goldin, 2007, SPIE Medical Imaging.

Brightness and contrast adjustments for different tissue densities in digital chest radiographs

Michael F. McNitt-Gray, Ricky K. Taira, Mahmood Razavi, 1991, Medical Imaging.

Feature selection in the pattern classification problem of digital chest radiograph segmentation

H. K. Huang, Michael F. McNitt-Gray, James W. Sayre, 1995, IEEE Trans. Medical Imaging.

Automated classification of lung bronchovascular anatomy in CT using AdaBoost

Michael F. McNitt-Gray, Jonathan G. Goldin, Matthew S. Brown, 2007, Medical Image Anal..

Evaluation of airway measurements in phantom parenchyma and soft tissue regions

Michael F. McNitt-Gray, Jonathan G. Goldin, Robert A. Ochs, 2008, SPIE Medical Imaging.

Pattern classification approach to characterizing solitary pulmonary nodules imaged on high-resolution computed tomography

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1996, Medical Imaging.

A monte carlo-based simulation tool for modeling x-ray computed tomography physics: application to electron beam ct

Michael F. McNitt-Gray, J DeMarco, Christopher H. Cagnon, 2003 .

Application of image analysis techniques to distinguish benign from malignant solitary pulmonary nodules imaged on CT

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1998, Medical Imaging.

Tradeoffs in helical CT: the effects of collimation and pitch on dose, noise, and slice sensitivity profiles

Michael F. McNitt-Gray, Chris H. Cagnon, Tim D. Solberg, 1996, Medical Imaging.

Patient-specific models for lung nodule detection and surveillance in CT images

Michael F. McNitt-Gray, Jonathan G. Goldin, Robert D. Suh, 2001, IEEE Transactions on Medical Imaging.

Computer-aided diagnosis of the solitary pulmonary nodule imaged on CT: 2D, 3D, and contrast enhancement features

Michael F. McNitt-Gray, Jonathan G. Goldin, Robert D. Suh, 2001, SPIE Medical Imaging.

Extensible knowledge-based architecture for segmenting CT data

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1998, Medical Imaging.

Respiratory-triggered electron beam CT with integrated spirometry for evaluation of dynamic airflow

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1996, Medical Imaging.

Automatic removal of unexposed background in digital radiographs

Michael F. McNitt-Gray, H. K. Huang, James Tagawa, 1992, Medical Imaging.

Effects of collimation and reconstruction algorithm on noise using low-dose lung cancer screening CT techniques

Michael F. McNitt-Gray, Kirsten L. Boedeker, Chris H. Cagnon, 2003, SPIE Medical Imaging.

Iterative reconstruction for low dose CT using Plug-and-Play alternating direction method of multipliers (ADMM) framework

Michael F. McNitt-Gray, Ryan Neph, Dan Ruan, 2019, Medical Imaging: Image Processing.

Dependence of CT attenuation values on scanner type using in vivo measurements

Michael F. McNitt-Gray, Jonathan G. Goldin, Fereidoun Abtin, 2008, SPIE Medical Imaging.

Preprocessing functions for computed radiography images in a PACS environment

Michael F. McNitt-Gray, H. K. Huang, Ewa Pietka, 1992, Medical Imaging.

Knowledge-based automated technique for measuring total lung volume from CT

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1996, Medical Imaging.

Multiscale shape features for classification of bronchovascular anatomy in CT using AdaBoost

Michael F. McNitt-Gray, Jonathan G. Goldin, Matthew S. Brown, 2007, SPIE Medical Imaging.

CAD in clinical trials: Current role and architectural requirements

Sumit K. Shah, Michael F. McNitt-Gray, Jonathan G. Goldin, 2007, Comput. Medical Imaging Graph..

Computer-aided lung nodule diagnosis using a simple classifier

Sumit K. Shah, Michael F. McNitt-Gray, Kheshini R. DeZoysa, 2004, CARS.

Computer-aided characterization of solitary pulmonary nodules (SPNs) using structural 3D, texture, and functional dynamic contrast features

Yang Wang, Sumit K. Shah, Michael F. McNitt-Gray, 2007, SPIE Medical Imaging.

The effects of slice thickness and radiation dose level variations on computer-aided diagnosis (CAD) nodule detection performance in pediatric chest CT scans

Michael F. McNitt-Gray, Matthew S. Brown, Pechin Lo, 2017, Medical Imaging.

SU-E-I-35: Development of Stand-Alone Filtered Backprojection and Iterative Reconstruction Methods Using the Raw CT Data Exported From Clinical Lung Screening Scans

Michael F. McNitt-Gray, Frédéric Noo, John M. Hoffman, 2015 .

Automated assessment of split lung functon in post-lung-transplant evaluation

Michael F. McNitt-Gray, Jonathan G. Goldin, Denise R. Aberle, 1998, Medical Imaging.

Enhancing 4d Cardiac Mri Registration Network With A Motion Prior Learned From Coronary Cta

Minsong Cao, Michael F. McNitt-Gray, Dan Ruan, 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

Comprehensive Methodology for the Evaluation of Radiation Dose in X-Ray Computed Tomography

John M. Boone, Michael F. McNitt-Gray, Dianna D. Cody, 2010 .

Pattern classification approach to segmentation of chest radiographs

Michael F. McNitt-Gray, James Sayre, H. K. Huang, 1993 .

ACR–STR Practice Parameter for the Performance and Reporting of Lung Cancer Screening Thoracic Computed Tomography (CT): 2014 (Resolution 4)*

Michael F. McNitt-Gray, Ella A. Kazerooni, William C. Black, 2014, Journal of thoracic imaging.

Radiation dose in Spiral CT: The relative effects of collimation and pitch

Timothy D. Solberg, Michael F. McNitt-Gray, Indrin J. Chetty, 1999 .

Tradeoffs in CT Image Quality and Dose

Michael F. McNitt-Gray, 2003 .

RECORDS: improved Reporting of montE CarlO RaDiation transport Studies.

Michael F. McNitt-Gray, Wesley E. Bolch, Ioannis Sechopoulos, 2018, International journal of radiation oncology, biology, physics.

TU‐EF‐204‐01: Accurate Prediction of CT Tube Current Modulation: Estimating Tube Current Modulation Schemes for Voxelized Patient Models Used in Monte Carlo Simulations

Michael F. McNitt-Gray, Cynthia H. McCollough, Kyle McMillan, 2015 .

Medical Image Interpretation

Michael F. McNitt-Gray, Matthew S. Brown, 2000 .

A Comparison of Different Size Metrics for Pulmonary Nodule Measurements 1

Geoffrey McLennan, Michael F. McNitt-Gray, Denise R. Aberle, 2007 .