Nicholas J. Tustison

Timeline

1. 1998–2004

   Degrees in physics and engineering

   He earns a BS in applied physics with a computer science emphasis at Brigham Young University in 1998 and an MS in biomedical engineering at the University of Virginia in 2000. A DSc in biomedical engineering from Washington University in St. Louis follows in 2004.

2. 2010

   The N4ITK bias correction

   In 2010, he is first author of N4ITK: Improved N3 Bias Correction, written with Brian Avants, James Gee and other colleagues in the University of Pennsylvania's Department of Radiology. The paper proposes a fast and robust B-spline approximation routine and a modified hierarchical optimization scheme to improve on the N3 bias field correction algorithm, and it releases the code through the National Institutes of Health's Insight Toolkit.

3. 2013

   Winning the BRATS 2013 challenge

   In 2013, he and colleagues Max Wintermark, Chris Durst and Brian Avants finish first in the Multimodal Brain Tumor Segmentation challenge at the MICCAI conference (BRATS 2013). Their entry builds on random forest approaches to segmentation.

4. 2019

   Convolutional networks for lung imaging

   In 2019, he is first author of two deep learning papers: a review of learning image-based spatial transformations with convolutional neural networks in Magnetic Resonance Imaging, and a study of convolutional neural networks with template-based data augmentation for functional lung image quantification in Academic Radiology.

5. April 2021

   The ANTsX ecosystem paper

   In April 2021, he is first author of The ANTsX ecosystem for quantitative biological and medical imaging in Scientific Reports. The paper describes ANTs, founded in 2008 around the Symmetric Normalization registration framework, and the ANTsRNet and ANTsPyNet deep learning extensions built on TensorFlow/Keras, including a deep learning pipeline for cortical thickness from T1-weighted brain MRI.

6. April 2024

   ANTsX phenotypes for UK Biobank

   In April 2024, he is first author of ANTsX neuroimaging-derived structural phenotypes of UK Biobank in Scientific Reports, written with Michael A. Yassa and colleagues. The paper adds ANTsX cortical, subcortical, medial temporal lobe and cerebellum measurements to the UK Biobank imaging-derived phenotypes and tests them by predictive modeling against age, fluid intelligence and numeric memory. He holds affiliations in both the University of Virginia's Department of Radiology and Medical Imaging and UC Irvine's Department of Neurobiology and Behavior.

7. As of October 2026

   Associate Professor at Virginia

   In November 2025, he is first author of The ANTsX ecosystem for mapping the mouse brain in Nature Communications, which aligns MERFISH spatial transcriptomics and fMOST morphology data to the Allen Common Coordinate Framework and introduces a deep learning framework for automated brain parcellation. He is an Associate Professor of Radiology and Medical Imaging at the University of Virginia, where his research covers neuroradiology projects, pulmonary research with hyperpolarized gases, and open-source image analysis algorithms.