- Gabor Fichtinger, Purang Abolmaesumi, David Gobbi, Siddharth Vikal; Queen’s University
- Allen Tannenbaum, Yi Gao; Georgia Tech
- Katie Hayes, Brigham and Women's Hospital
For the task of prostate segmentation, we provide two tools: 1. shape based and 2. semi-automatic random walk based. The goal is to put both algorithm into Slicer3.
Algorithm 1. is a Shape based segmentation. The shape of prostates are learned and then the new image is segmented using the shapes learned. Algorithm 2. is based on the Random Walks segmentation algorithm. It need more human input but the result could be interactively improved arbitrarily close to user's expectation.
During the project week, we achieved:
- Integrated semi-auto algorithm (algorithm 2) into Trans Rectal Prostate biopsy interactive loadable module, shown in the middle figure above.
- Integrated shape based algorithm (algorithm 1) into Slicer3 as command line module, shown in the right figure above.