Perelman School of Medicine at the University of Pennsylvania


Seed Grants

In the first 3 years we had great success with our seed grants program, and at least 3 of the seed grants have already contributed to funded or to-be-funded R01s. Last year the focus of our seed grant program switched to making imaging analytic tools more translation-oriented, via practical software implementation. This year we will continue along this direction. We now have a software engineer/programmer team in place, and the seed grants will be given as percent-effort of one programmer, in order to help translate mature computational algorithms or analysis pipeline into tools that can be more easily used in the clinic. For basic elements, important dates, and application materials see the application details below.

2017 Awardees
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

Application Details

Important dates:

  • Sunday, May 7, 2017: Deadline for submission
  • July 10, 2017: Announcement of awards
  • October 1, 2017: Award start date

Basic Elements:

  • Suitable projects will have the basic science and validation part already completed in prior work, and will be ready for translation.
  • Translation can be achieved in many ways: by augmenting a pipeline with a user-friendly front-end, documenting it appropriately, and creating a ready-to-install program; by using our image processing web portal (, which allows us to "export" pipelines running on our server and make them readily available to outside users via submitting images and receiving results; by building a plug-in for an existing clinical workstation or other visualization means (e.g. mevislab); or via some other suitable way.
  • CBICA faculty and senior postdocs are eligible to apply: the latter are particularly encouraged to do so, if they have a method that is mature and suitable for translation.

Application Materials:

  • 2-page description of the project, documenting the existing method with evidence that it is mature and suitable for translation
  • A detailed plan on the translational implementation utilizing ~40% effort of the programmer
  • Biosketches
  •  Please send all material to Amanda Shacklett


Past Awardees


  • 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"


  • 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"


  • 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"


  • 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"