Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Large scale visualization on the Powerwall.
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

Events on January 14, 2019

Imaging Seminar

Blake Zimmerman, PhD Student Presents:

Registration of Magnetic Resonance Imaging and Volumetric Histology for Quantitative Assessment of Thermal Therapies

January 14, 2019 at 12:00pm for 1hr
Meldrum Conference Room, WEB 2760
Warnock Engineering Building, 2nd floor.

Abstract:

Surgical removal of localized cancers has evolved from highly-invasive surgeries to conservative interventions. For example, removal of localized breast cancer has matured from invasive mastectomies to breast conservation surgeries. The next step in conservative localized cancer interventions is non-invasive ablation treatments. Magnetic resonance (MR) guided thermal ablation treatments are promising non-invasive interventions for localized cancer. Without surgical removal of the cancer, accurately defining the non-viable tissue after thermal ablation is paramount to guarantee the entire cancer volume is treated. MR guidance provides structural information for treatment planning, real-time thermal maps to monitor treatment, and multi-parametric images for assessing treatment. However, clinical metrics for assessing treatment outcomes do not always predict the same non-viable volume and can over- or under-estimate the actual treated volume. Current clinical metrics are not sufficient for localized cancer treatment assessment.

The gold standard for defining non-viable tissue is histopathology. Validating quantitative MR metrics will require treat and resect trials that compare acquired MR images to gold standard histopathology. However, processing resected tissue for histopathology introduces unknown deformations, including orientation loss during tissue extraction, shrinkage from tissue fixation, and shearing/stretching from microscopic sectioning. Current registration methods for validating MR metrics against histopathology do not correct for tissue deformations at every stage of histology processing. This research will develop accurate MR to histology registration methods to enable rigorous evaluation of quantitative MR metrics for thermal treatment assessment. This new technique will provide the critical tools needed to validate quantitative imaging techniques that can accurately predict clinical outcomes in image guided cancer treatments.

Posted by: Praful Agrawal