Weakly-Supervised Learning via Multi-Lateral Decoder Branching for Guidewire Segmentation in Robot-Assisted Cardiovascular Catheterization

arXiv:2404.07594v1 Announce Type: cross
Abstract: Although robot-assisted cardiovascular catheterization is commonly performed for intervention of cardiovascular diseases, more studies are needed to support the procedure with automated tool segmentation. This can aid surgeons on tool tracking and visualization during intervention. Learning-based segmentation has recently offered state-of-the-art segmentation performances however, generating ground-truth signals for fully-supervised methods is labor-intensive and time consuming for the interventionists. In this study, a weakly-supervised learning method with multi-lateral pseudo labeling is proposed for tool segmentation in …

abstract art arxiv automated cs.cv cs.lg cs.ro decoder diseases robot segmentation state studies supervised learning support tool tracking type via visualization weakly-supervised