Semi-supervised Segmentation of Organs and Tumors in 4D-CT

• Abstract

  Radiation therapy of tumors relies on 3D-CT and 4D-CT treatment planning imagery which is manually segmented (delineated) and labeled prior to the optimization of the dose delivery plan. Automatic segmentation of all regions of interest has been a topic of intense research interest yet clinical practitioners are unsatisfied with the performance of existing solutions.

• Description

  Radiation therapy of tumors relies on 3D-CT and 4D-CT treatment planning imagery which is manually segmented (delineated) and labeled prior to the optimization of the dose delivery plan. Automatic segmentation of all regions of interest has been a topic of intense research interest yet clinical practitioners are unsatisfied with the performance of existing solutions. It is our goal to keep the clinician in the loop during the process and design an interactive segmentation tool that fuses inputs from the expert user with low level features in imagery to speed up the manual delineation process. One important goal is to accurately transfer object boundaries from one respiration phase of 4D-CT to the other without performing 3D-to-3D deformable registration.

• Team Members