Perelman School of Medicine at the University of Pennsylvania

CBICA

Seed Grants


The Center for Biomedical Image Computing and Analytics (CBICA) will offer a 1-year seed grant, at a budget level of $50,000. This mechanism aims to support innovative work likely to lead to novel and impactful new directions. Synergies between basic scientists and clinicians are encouraged. Priority will be given to proposals that are likely to lead to NIH funding, as well as projects that are likely to catalyze collaborations across disciplines. Applicants at the postdoc or research associate level are encouraged, but should have a faculty mentor undersigning the application. Faculty on the selection committee (Christos Davatzikos and David Mankoff) cannot participate in any seed grant. Start date is expected to be Jan. 1, 2019.

2018 Awardees
   
   
   
   

Application Details

Important dates:

  • Sunday, November 25, 2018: Deadline for submission
  • January 1, 2019: Award start date (1 year)

 

Application Materials:

  • 2-page description of the project
  • A detailed plan
  • Biosketches
  • Please send all material to Jessica Incmikoski

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Past Awardees

2017

  • Spyridon Bakas, Hamed Akbari, Gaurav Shukla, Robert Lustig: "Refined Personalized Radiotherapy Target Volume Definition using  Predictive Recurrence maps in Glioblastoma"
  • Aimilia Gastounioti, Tessa S. Cook, Emily Conant: "LIBRA platform: Translational implementation of quantitative imaging phenotypes for breast cancer masking and risk"
  • Theodore D. Satterthwaite, Danielle S. Bassett, Phillip Cook, Nicolas Honnorat, Yong Fan: "Creating a Scalable Infrastructure to Accelerate Clinical Applications of Functional Connectomics"

2016

  • Jimit Doshi, Michel Bilello: "Computer-Aided Detection for Monitoring Aneurysm Progression (CADMAP) for Clinical Use"
  • Guray Erus, Jimit Doshi, Michel Bilello: "An Integrated Tool for Quantitative Profiling of Brain Structure towards MRI-based Personalized Medicine"
  • Despina Kontos, Aimilia Gastounioti: "Laboratory for Breast Radiodensity Assessment” (LIBRA): A software tool for the translation of novel quantitative imaging biomarkers into personalized breast cancer risk assessment"
  • Jared Pisapia, Gregory G. Heuer, Deborah Zarnow: "Fetal Ventriculomegaly: Developing software to predict the clinical need for shunting"
  • Theodore D. Satterthwaite, Aristeidis Sotiras: "Characterization of regional neurodevelopment in adolescence through non-negative pattern analysis"

2015

  • Michelle Johnson, Ragini Verma: "Neural and Motor Functional Changes in HIV and Stroke before and after Robot-Assisted Neurorehabilitation"
  • Brad Keller, Michael Feldman: "Histological Determinants of Radiographic Breast Cancer Risk Factors"
  • Jared Pisapia, Michel Bilello: "Predicting optic pathway glioma progression via advanced image analysis and machine learning"

2014

  • Danielle S. Bassett, James Gee: "Linked Structure-Function Predictors of Frontotemporal Dementia Pathology"
  • Theodore D. Satterthwaite, Russell T. Shinohara: "Flexible Nonlinear Modeling of Normal and Abnormal Neurodevelopment in Adolescence"

2013

  • Kathryn Davis, Paul Yushkevich: "Hippocampal Subfield Volumetric and Functional Connectivity on 7T MRI: Potential Biomarkers in Medically Refractory Temporal Lobe"
  • Despina Kostos, Angela DiMichele: "Quantitative Characterization of Spatio-temporal Tumor Heterogeneity via 4D Breast DCE-MRI Registration as a Biomarker of Response to Neoadjuvant Chemotherapy"
  • Luke Macyszyn, Ragini Verma: "Automated Tractography for Neuro-Oncology: Resolving the challenges of Edema, Mass Effect and Seed Placement"

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