Vision guided automation for intra-cytoplasmic sperm injection
Biological cell injection is an effective technique in which a foreign material is directly introduced into the target cell. Intracytoplasmic Sperm Injection (ICSI) is a microinjection technique which is used for infertility treatment. In this technique, a single sperm cell is directly injected into an oocyte using micropipettes. The operations in this application are manually controlled by an embryologist and more importantly, this reduces the accuracy, repeatability, and consistency of the operation. Therefore, the full automation is a prerequisite for microinjection operations, particularly in ICSI application. This thesis focuses on enhancing the microinjection procedure by developing vision-guided processes prior to and during the operation. Initially, a vision-controlled technique was proposed to align the injection and holding pipettes in three orthogonal axes which is essential for successful microinjection. To conduct reliable injection, the vibrational displacement of the injection pipette’s tip needs to be evaluated and improved before the operations continue further. A novel vision-based sensor was developed to measure the displacement changes at the tip in three orthogonal axes. By employing the developed vision sensor, the effect of injection speed on vibrational displacement creation was analysed to determine the value of various injection parameters, such as force fluctuation, and penetration force on cell damages. An ultimate automation task is required in microinjection to position the randomly located biological cell within the Petri dish to the system’s field of view. The proposed technique fills a gap in the literature by proposing a real-time cell recognising and positioning system that can be employed with different types of biological cells at various maturation stages, as well as with different microscope types that are being used in microinjection applications.
http://etheses.bham.ac.uk//id/eprint/11327/7.hassmallThumbnailVersion/Sadak2021PhD.pdf
http://etheses.bham.ac.uk//id/eprint/11327/7/Sadak2021PhD.pdf