O
Omkar Dandekar
Researcher at University of Maryland, Baltimore
Publications - 23
Citations - 400
Omkar Dandekar is an academic researcher from University of Maryland, Baltimore. The author has contributed to research in topics: Image registration & Image processing. The author has an hindex of 11, co-authored 23 publications receiving 384 citations. Previous affiliations of Omkar Dandekar include Intel & University of Maryland, College Park.
Papers
More filters
Journal ArticleDOI
Live augmented reality: a new visualization method for laparoscopic surgery using continuous volumetric computed tomography
Raj Shekhar,Raj Shekhar,Omkar Dandekar,Omkar Dandekar,Venkatesh Bhat,Venkatesh Bhat,Mathew Philip,Mathew Philip,Peng Lei,Peng Lei,Carlos Godinez,Erica Sutton,Ivan George,Steven Kavic,Reuben Mezrich,Adrian Park +15 more
TL;DR: The authors proposed and developed live AR, a new surgical visualization approach that merges rich surface detail from a laparoscope with instantaneous 3D anatomy from continuous CT scanning of the surgical field from continuous multislice computed tomography.
Journal ArticleDOI
FPGA-Accelerated Deformable Image Registration for Improved Target-Delineation During CT-Guided Interventions
Omkar Dandekar,R. Shekhar +1 more
TL;DR: A field-programmable gate array-based architecture for accelerated implementation of mutual information (Ml)-based deformable registration is presented, which reduces the execution time of MI-based deformables registration from hours to a few minutes and is suitable for integration in the IGI-workflow.
Patent
Real-time Elastic Registration to Determine Temporal Evolution of Internal Tissues for Image-Guided Interventions
TL;DR: In this article, an elastic transform is determined that registers the first scan data elastically to the second scan data, and a particular spatial arrangement of the moving target tissue is indicted based on the elastic transform.
Patent
Method and apparatus for accelerated elastic registration of multiple scans of internal properties of a body
TL;DR: In this paper, a local joint histogram of mutual information based on the reference scan data and the floating scan data for the subset is determined and subtracted from an overall joint Histogram to determine a remainder joint HOG.
Journal ArticleDOI
FPGA-based real-time 3D image preprocessing for image-guided medical interventions
TL;DR: A field-programmable gate array-based reconfigurable architecture for real-time preprocessing of intraoperative 3D images and provides programmable kernels for 3D anisotropic diffusion filtering and 3D median filtering within the same framework is presented.