Jerrold L. Boxerman

发表

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials

Natenael B. Semmineh, Ashley M. Stokes, Laura C. Bell, 2017, Tomography.

Susceptibility Effects in Whole Body Experiments

Bruce R. Rosen, Robert M. Weisskoff, Jerrold L. Boxerman, 2007 .

Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach

Jiye G. Kim, William Lotter, A. Gregory Sorensen, 2019, ArXiv.

Variable block-sized vector quantization of gray-scale images with unconstrained tiling

Jerrold L. Boxerman, Ho John Lee, 1990, Other Conferences.

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)

Thomas E. Yankeelov, Chengyue Wu, Mark Muzi, 2019, Tomography.

Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge

Thomas E. Yankeelov, Chengyue Wu, Mark Muzi, 2020, Tomography.

Principles of T2*‐weighted dynamic susceptibility contrast MRI technique in brain tumor imaging

James M. Provenzale, Max Wintermark, Meng Law, 2015, Journal of magnetic resonance imaging : JMRI.

Standardized Brain Tumor Imaging Protocol for Clinical Trials

Daniel P. Barboriak, Jerrold L. Boxerman, Mark R. Gilbert, 2015, American Journal of Neuroradiology.

Is Rolandic epilepsy associated with abnormal findings on cranial MRI?

Jerrold L. Boxerman, Deb K. Pal, J. Boxerman, 2007, Epilepsy Research.

An Efficient Computational Approach to Characterize DSC-MRI Signals Arising from Three-Dimensional Heterogeneous Tissue Structures

Paul W. Cleary, John C. Gore, Gary W. Delaney, 2014, PloS one.