| Literature DB >> 26478693 |
Yen-Chi Chang1, Brittany Berry-Pusey2, Rashid Yasin3, Nam Vu2, Brandon Maraglia2, Arion X Chatziioannou2, Tsu-Chin Tsao1.
Abstract
This paper develops an automated vascular access system (A-VAS) with novel vision-based vein and needle detection methods and real-time pressure feedback for murine drug delivery. Mouse tail vein injection is a routine but critical step for preclinical imaging applications. Due to the small vein diameter and external disturbances such as tail hair, pigmentation, and scales, identifying vein location is difficult and manual injections usually result in poor repeatability. To improve the injection accuracy, consistency, safety, and processing time, A-VAS was developed to overcome difficulties in vein detection noise rejection, robustness in needle tracking, and visual servoing integration with the mechatronics system.Entities:
Keywords: Image processing; injection robot; marine vein detection; needle guidance
Year: 2014 PMID: 26478693 PMCID: PMC4607285 DOI: 10.1109/TMECH.2014.2360886
Source DB: PubMed Journal: IEEE ASME Trans Mechatron ISSN: 1083-4435 Impact factor: 5.303