Dr. Juan Carlos Prieto

Individual Member | Research Assistant Professor at Univ of North Carolina at Chapel Hill
Prieto, Juan Carlos
SPIE Leadership: Retrieving Data, please wait...
SPIE Membership: 5.3 years
SPIE Involvement: Retrieving Data, please wait...
Area of Expertise: Image Analysis, 3D Shape Analysis, Deep learning
Contact Details:
Sign In to send a private message or view contact details

Profile Summary

Dr. Prieto is a leading expert in data science with specific expertise in data curation, management, and the development of robust algorithms that include artificial intelligence approaches. In his experience as a research associate at Brigham and Women's Hospital, he initiated the development of a framework to create/manage, and annotate medical images. Since his arrival at UNC in 2015, under Martin Styner’s senior mentoring at UNC, he has been the lead developer of 3D Slicer craniomaxillofacial tools working under Dr. Cevidanes NIDCR funded R01 DE024450 at the University of Michigan. He has since then collaborated in multi-center studies and developed novel algorithms for decision support tools that include 3D object modeling, visualization, and shape statistical analysis, user-friendly tools to facilitate testing of their clinical performance. Dr. Prieto has overseen the last 4 major releases of SlicerCMF (Cranio Maxillo Facial) software.

As part of Dr. Prieto’s neuroimage developments, he has supervised the development of software tools for brain image analysis such as MultiSegPipeline, FADTTSter (diffusion imaging, fiber tract statistics), and tools to calculate the cerebral spinal fluid (CSF) in the developing brain.

Dr. Prieto's ongoing collaboration with Dr. Jeffrey Stringer at the Obstetric and Gynecology Department at UNC lead to the development of an algorithm to predict the gestational age of a fetus using blind sweep ultrasound videos. The ultimate goal of this study is to improve the healthcare outcomes of mothers and children in developing countries.

Dr. Prieto's ongoing collaboration with Dr. Emily Gower at the department of Epidemiology at UNC lead to the development of an algorithm to detect trachomatous trichiasis (TT) using the standard camera from conventional smartphones. TT is the leading cause of blindness worldwide. This mobile application is currently being tested in Ethiopia.

Upcoming Presentations

Most Recent | Show All
Retrieving Data, please wait...

Publications

Most Recent | Show All
Retrieving Data, please wait...

Conference Committee Involvement

Most Recent | Show All
Retrieving Data, please wait...

Course Instructor

Most Recent | Show All
Retrieving Data, please wait...
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research