Faculty

Contact Information
  • henry.rusinek@nyulangone.org
  • 212-263-6537

Henry Rusinek, PhD

Professor

The rapid improvement of high-resolution MR, CT, and PET imaging has expanded our knowledge of the structure and function of the human body. With novel images analysis methods, we can achieve a deeper understanding of normal and diseased states.

Our main goal is to develop innovative image analysis and modeling tools to support clinical research studies. This is achieved by multidisciplinary collaboration between basic scientists, engineers, and physicians.

Here are some of our areas of interest:

  • the development of compartmental models based on dynamic MR/PET/CT imaging
  • image coregistration and segmentation algorithms
  • the analysis of image texture

Research Projects

Multi-Scale and Multi-Modality Imaging of Neuropathology in VCID

This study aims to advance understanding of neurodegeneration in VCID by developing postmortem MRI protocols, computational tools, and multi-modal atlases, standardizing MRI and histology methods, and creating extensive imaging and biomaterial resources to support research in AD, ADRD, and related pathologies.

Aging

FireVoxel: Interactive Software for Multi-Modality Analysis of Dynamic Medical Images

FireVoxel is a freely distributed medical imaging analysis software developed at NYU Langone that provides powerful quantitative tools—especially for dynamic abdominal and genitourinary studies—and has become widely adopted in MRI research worldwide.

Quantitative MRI

Neuroimaging Core of NYU Langone’s Alzheimer’s Disease Research Center

The neuroimaging core of NYU Langone’s Alzheimer Disease Research Center supports research on Alzheimer’s and related dementias by developing and applying advanced imaging techniques to aid early diagnosis, track disease progression, and inform novel diagnostics and treatments.

Aging

Breast cancer Intravoxel Incoherent Motion Multisite (BRIMM) Project

The BRIMM project is a multi-site breast cancer study using intravoxel incoherent motion (IVIM) MRI to develop a robust, cross-platform imaging biomarker that noninvasively characterizes the tumor microenvironment and predicts response to neoadjuvant chemotherapy.

Breast

Advanced Diffusion MRI in Renal Cancer: Oncologic Control and Renal Functional Reserve

This project investigates REFMAP, an advanced diffusion MRI approach combining IVIM and DTI, to noninvasively diagnose kidney tumors, estimate glomerular filtration rate, and predict renal function outcomes following surgery.

Diffusion MRI

Researchers at the Center for Biomedical Imaging at NYU Langone Health develop transformative imaging technologies to advance basic science and address unsolved clinical problems.

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