Abstract:

Pelvic floor disorders affect an important number of women. They are characterized by a debilitating mechanical stability of pelvic organs. This brings symptoms that disturb immensely the patient’s quality of life. Available treatment options range from drug therapy, to implants and in some cases surgical repair. To maximize the success of surgery and reduce the probability of recurrence a precise planning based on Medical Imaging is required. Traditional techniques such as Fluoroscopy, Ultrasound and Magnetic Resonance Imaging are normally used for qualitative assessment of pelvic floor disorders. The aim of this project is to perform a quantitative assessment of pelvic organ deformation using a shape descriptor based on image moments. A novel method of acquisition was used for imaging of the pelvic organs. Semiautomatic, segmentation was done, coupled with an interpolation method to reconstruct 3D volumes of the bladder. A shape descriptor based on Zernike moments was implemented and tested based on two different algorithms: Novotni and Pozo. Simulation and in vivo experiments were performed on the bladder to validate its performance. Deformation maps are proposed as a method for visualization of the dynamic deformations of the bladder. The Novotni method showed a better visualization of the deformations for every case, the Pozo method only showed a clear correlation when used with the simulated data.