Image Mosaicking Using Vessel Segmentation for Application During Fetoscopic Surgery

• Main Author: Grönberg, Axel
• Format: Others
• Language: English
• Published: Uppsala universitet, Institutionen för informationsteknologi 2021
• Subjects: Engineering and Technology; Teknik och teknologier
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-438422

Twin-to-twin-transfusion syndrome is a condition where there is an imbalance in the shared blood circulation between monochorionic twin fetuses due to certaininter-twin vascular connections (anastomoses) in the placenta which has very high morbidity and mortality rate for both fetuses. Fetoscopic laser occlusive coagulation(FLOC) surgery is commonly used to treat the condition which uses a fetoscope to explore the placenta and a laser to occlude the anastomoses causing the imbalance inblood circulation. In order to deal with the navigational difficulties caused by the limited field of view of the fetoscope, this thesis is part of a work towards an application which main purpose is to build a global map of the placenta as well as display position of the fetoscope on that map. A combination of segmentation by neural networks are combined with direct sequential registration techniques are applied to fetoscopic data from FLOC surgeries at Karolinska University Hospital Huddinge and resulting in a proof-of-concept of this mosaicking pipeline setup for the creation of a global map of the placenta during such a surgery. It was however also found that more work is needed to make the system more reliable and among other things less sensitive to poor visual conditions and drift, which can result in low quality mosaics with artifacts due to misaligned images.