Scott Trinkle

Scott Trinkle

Data scientist based in Chicago, IL

All News Posts

New preprint: Model-based vs. model-free myelin imaging

My latest manuscript uses model-free analysis of echo-planar spectroscopic imaging to show that fitting data to common biophysical models lowers myelin classification performance.

New position: Data Engineer at Waters Corporation

I have been hired as a Machine Learning Intern at Waters Corporation, where I will be developing python web apps for mass spectrometry imaging.

Ph.D Thesis defense

I successfully defended my thesis entitled "Multi-modal validation of MR microstructure imaging in the mouse brain.

New paper: Geometric bias in mouse brain networks from diffusion MRI

My new manuscript uses graph theory and optical tracer imaging to show that many properties of structural mouse brain networks measured with diffusion MRI can be largely explained through their spatial embedding alone, revealing geometric biases in diffusion tractography.

Paper highlight: Figure chosen for cover of Magnetic Resonance in Medicine

Our figure displaying spatial registration results between microCT and diffusion MRI is featured on the August 2021 cover.

Article: Research highlighted in UChicago News

The article focuses on our imaging pipeline connecting MRI to electron microscopy in the same sample using synchrotron microCT.

New position: Machine learning internship at Waters Corporation

I have been hired as a Machine Learning Intern at Waters Corporation, where I will be developing python web apps for mass spectrometry imaging.

New paper: Imaging a single mouse brain over five orders of magnitude of resolution

Our new manuscript describing a multi-modal microstructural imaging pipeline was published in NeuroImage.

New paper: feature extraction from a 1 TB microCT image and spatial registration to diffusion MRI

My new paper was just published in Magnetic Resonance in Medicine. It demonstrates a processing pipeline to validate diffusion MRI with microCT.

Presentation: Received Magna Cum Laude merit award for talk at virtual ISMRM 2020 conference

My talk was entitled "Synchrotron microCT tractography connectomics: comparison with diffusion MRI and neural tracer injections".

Presentation: Colloquium talk for the UChicago Graduate Program in Medical Physics

I was invited to give a talk to the department entitled "Multi-modal validation of diffusion MRI tractography".

Award: F31 predoctoral fellowship from the NIH

I have been awarded a fellowship for my thesis project entitled "A novel multi-modal, multi-scale imaging pipeline for the validation of diffusion MRI of the brain".

Presentation: Received Magna Cum Laude merit award for talk at ISMRM 2019 conference in Montréal

My talk was entitled "X-ray microcomputed tomography as a natively isotropic, nondestructive, 3D validation dataset for diffusion MRI".

Presentation: Gordon Research Conference on Image Science

I attended the conference with a poster presentation called "Towards whole-brain validation of diffusion MRI fiber-orientation distributions with x-ray microcomputed tomography".