For the stable Slicer documentation, visit the 4.6 page.
Introduction and Acknowledgements
SlicerProstate extension hosts various modules to facilitate
- processing and management of prostate image data
- utilizing prostate images in image-guided interventions
- development of the imaging biomarkers of the prostate cancer
While the main motivation for developing the functionality contained in this extension was prostate cancer imaging applications, they can also be applied in different contexts.
- Distance Map Based Registration: module that can be used for deformable registration between prostate gland segmentations in MR and TRUS
- Segmentation Smoothing: module to smooth the staircase aliasing effect commonly found in prostate segmentations done in typical MRI data
- QuadEdgeSurfaceMesher: module to reduce the number of triangles and smooth the surface recovered with the Marching Cubes algorithm
- DWModeling: module to fit commonly used models to Diffusion Weighted MRI of the prostate
 Fedorov A, Khallaghi S, Antonio Sánchez C, Lasso A, Fels S, Tuncali K, Neubauer Sugar E, Kapur T, Zhang C, Wells W, Nguyen PL, Abolmaesumi P, Tempany C. (2015) Open-source image registration for MRI–TRUS fusion-guided prostate interventions. Int J CARS: 1–10. Available: http://link.springer.com/article/10.1007/s11548-015-1180-7.
 Fedorov A, Nguyen PL, Tuncali K, Tempany C. (2015). Annotated MRI and ultrasound volume images of the prostate. Zenodo. http://doi.org/10.5281/zenodo.16396
 Kobus T., Fedorov A., Tempany C.M., Mulkern R.V., Dunne R., Maier S.E. Bi-exponential Diffusion Analysis in Normal Prostate and Prostate Cancer: Transition Zone and Peripheral Zone Considerations. Proc. of ISMRM 2015. http://www.spl.harvard.edu/abstracts/item/view/168
Information for Developers
- SlicerProstate organization page on github: https://github.com/SlicerProstate