Funding
Current Funding
We are thankful to our supporters for their vision and commitment to our research.
NIH NCI UH3-UG3CA236536
"Quantitative MRI for Pediatric Optic Pathway Glioma Treatment Response"
Imaging tools for longitudinal measures of tumor volume critical for the assessment of treatment response.
DoD NF180067
"MRI Volumetrics for Risk Stratification of Vision Loss in Optic Pathway Gliomas Secondary to NF1"
Develop image-based predictive markers of risk stratification of vision loss in neurofibromatosis type 1.
NIH NIDCR R00DE027993
"Quantitative characterization and predictive modeling of cranial bone development in craniosynostosis"
Career development award to create a cranial developmental model during childhood.
NIH NIBIB R13EB030422
"International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 2020"
Provide travel awards for students and early investigators with focus on minority and underrepresented
Philips Healthcare Award
"Ultrasound Quantification of Pediatric Hydronephrosis"
The goal of this study is to characterize pediatric hydronephrosis more precisely and without radiation by developing quantitative, robust and reproducible ultrasound-based techniques to evaluate hydronephrosis.
Research Advisory Council Grant/Sheikh Zayed Institute
"Quantitative Imaging Program"
The Quantitative Imaging Program aims to develop and validate quantitative image-based software tools that can assess disease, design personalized therapies and anticipate risk factors in the lives of children.
Past Funding (selected)
NIH NICHD R42 HD081712
"Image-Guided Planning System for Skull Correction in Children with Craniosynostosis"
The goal of this project is to develop personalized preoperative planning for cranial remodeling for infants with craniosynostosis via image and shape analysis to allow for decreased operative time and morbidity.
NIH NHLBI R41 HL145669
"Imaging Biomarkers of Severe Respiratory Infections in Premature Infants"
The goal of this project is to develop and evaluate a quantitative imaging technology to assess the risk for severe respiratory disease in premature babies using non-invasive low-radiation X-ray imaging.
NIH NIDCR K99DE027993
"Quantitative characterization and predictive modeling of cranial bone development in craniosynostosis"
Mentored career development award to create a cranial developmental model during childhood.
NSF I-Corps 1924125
"I-Corps: Early Risk Assessment of Infant Head Malformations at the Point-of-Care"
Perform customer discovery interviews for a smartphone app designed to detect cranial malformations.
Pediatric Innovation Fund/Children’s Hospital Foundation
"mGene – Early and Mobile Detection of Genetic Syndromes"
The project will develop and validate mobile technology for facial analysis for the early and non-invasive screening of dysmorphic genetic syndromes.
NIH NICHD R41 HD081712
"Image-Guided Planning System for Skull Correction in Children with Craniosynostosis"
The goal of this project is to develop personalized preoperative planning for cranial remodeling for infants with craniosynostosis via image and shape analysis to allow for decreased operative time and morbidity.
The Royal Society IES\R3\170219
"Multi-Organ Physiology-Adaptive Shape Model of the Abdomen"
This project aims to develop a spatiotemporal multi-organ deformable model of the abdomen, combining advanced techniques for multi-organ statistical analysis with deep learning-based techniques.
NIH NCATS UL1 TR001876/KL2 TR001877
"Quantitative Facial Morphology in Pediatric Populations in the Democratic Republic of the Congo"
The aims of this project are to collect normative and syndromic data to quantify and analyze normative facial features, and to determine discriminant facial features of Down syndrome in DRC population.
NIH NCATS UL1 TR001876/KL2 TR001877
"Reduced Dosage Acquisition of Computed Tomography Imaging for Pediatric Metastatic Diseases"
We propose to develop a novel deep learning approach to obtain diagnostic-quality CT images that are adequate for the early detection of pulmonary nodules using low radiation dosage acquisition protocols.
Gilbert Family Neurofibromatosis Institute
"Eliminating Vision Loss and Imaging"
The goal of this project is to develop and validate volumetric quantitative imaging markers of risk stratification of vision loss in children with neurofibromatosis and optic pathway gliomas.
Joseph E. Roberts Jr., Award/Center for Surgical Care
"Early Detection of Ureteropelvic Junction Obstruction using Signal Analysis and Machine Learning"
The project will improve the interpretation of dynamic information embedded in the renal drainage curves through developing signal processing and machine learning methods to assess disease severity.
KUIRF Award#1569969527, UAE
"Computer-Aided Diagnosis System for Early Detection of Infantile Dysmorphic Syndromes in the UAE"
The project aims to design and develop a simple and practical framework for the early and non-invasive detection of dysmorphic syndromes in newborns by novel imaging, genetic and data mining technologies.
NIH NCATS UL1TR000075/KL2TR000076
"Molecular, Clinical and Imaging Biomarkers of Severity of Viral Respiratory Illness in Children"
The project aims to develop molecular, clinical and computational imaging techniques that can identify trans-disciplinary biomarkers that predict severity during viral respiratory infections in children.