Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

Research output: Contribution to journalArticle

Authors

  • Michael Jermyn
  • Hamid Ghadyani
  • Michael A Mastanduno
  • Wes Turner
  • Scott C Davis
  • Brian W Pogue

Colleges, School and Institutes

Abstract

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

Details

Original languageEnglish
Pages (from-to)86007
Number of pages1
JournalJournal of Biomedical Optics
Volume18
Issue number8
Publication statusPublished - Aug 2013

Keywords

  • Algorithms, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Software, Spectroscopy, Near-Infrared, Tomography, Optical