Segmentation of ultrasound images for phlebotomy applications
Dipti Prasad Mukherjee, Scott T. Acton · 2014
A global solution to the enhancement and segmentation of ultrasound images is proposed that is operable in both low contrast and high contrast imaging scenarios. The solution is based on two optimization processes: one that minimizes error with respect to the original image while minimizing the number of edge contours (above the number expected by the known topology), and the second that maximizes edge fidelity. The maximization of edge fidelity is achieved by way of connected filters that operate on connected components of a threshold-decomposed image. To test the algorithm, an application in the ultrasound imaging of human blood vessels is explored. The results show significant improvements (8X to 50X) in a vesselness measure of the segmented vessels as compared to that yielded by a traditional speckle reduction technique and to a diffusion-based technique.