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Jeremy Magland

Jeremy Magland, Ph.D.

Research Assistant Professor of Radiologic Science

Department of Radiology
University of Pennsylvania Health System
1 Founders Building
3400 Spruce Street
Philadelphia, PA 19104
PH: (215) 349-5295
FX: (215) 662-7263

Dr. Magland develops and maintains a number of software frameworks and computational methods that are central to research in the Laboratory for Structural NMR Imaging

SequenceTree, pulse sequence programming environment for MRI:

SequenceTree is a graphical pulse sequence programming environment for MRI that was developed by Dr. Magland to improve the efficiency of developing and testing prototype research sequences on Siemens research scanners. This software can be used to design, create, visualize, and simulate pulse sequences, and then ultimately export them to run on a real MRI scanner. SequenceTree has been used within LSNI to create hundreds of sequences for a diversity of applications including ultra-short echo time (UTE) imaging of cortical bone, multi-shot fast spin-echo imaging of trabecular bone, spectroscopic imaging for quantification of lipid content in vertebral marrow, high temporal resolution dynamic blood oxymetry, and many others.

Web-Interactive Scientific Data Manager (WISDM):

WISDM is a web-based informatics framework for remote visualization, processing, and interactive sharing of MRI research results. This tool is currently being used to streamline analyses for various research projects at LSNI, including a dynamic pulse wave velocity measurement protocol, a spectroscopic imaging technique for quantifying lipid content in vertebral bone marrow, and MR image-based structural analysis of trabecular bone networks. In addition, WISDM is being used to share results of functional MRI studies between multiple investigators.

WISDM is a web-based framework for cloud-based visualization and processing of raw data, and for convenient sharing of results across multiple laboratories.

Real-time functional MRI:

Another focus of Dr. Magland’s research is optimization of real-time functional MRI techniques. Real-time fMRI feedback has been shown promise as a therapeutic tool for various cognitive disorders, but a principal challenge is overcoming the noise inherent in the real-time BOLD fMRI signal. Dr. Magland has recently developed novel multi-voxel classification strategies for providing high-SNR regional BOLD neuro-feedback.

Real-time functional MRI experiment highlighting the STAR technique for optimizing regional BOLD signal feedback. While feedback from the whole brain classifier (A) has the highest classification accuracy, the STAR technique provides region-specific feedback signals (C and D) with much higher SNR than the conventional regional BOLD technique (E and F).

Image-based mechanical modeling of trabecular bone:

Dr. Magland has also played a leading role in the development software for MR image-based finite-element modeling of the mechanical properties of trabecular bone. By optimizing memory usage and computation efficiency for this specialized application, this software allows large-scale finite-element simulations (normally requiring super-computing capabilities) to be performed using a standard workstation.