Pre-diagnosis of pelvic floor disorders-based image registration and clustering

Abstract

Pelvic dysfunction mainly affects adult women, it is estimated that 15% of multiparous women suffer from the problem. Dysfunctions can be diagnosed by defecography, a dynamic MRI scan. Images are used by specialists to diagnose organ dysfunction such as the bladder and the early rectum. This paper presents an automated classification system that uses a non-rigid registration based on a variational model to create automatic markings from initial markings made by an expert. The classification is based on simple average and the centroids of the K-means grouping technique. The classification made by the system is evaluated by confusion matrix based metrics. The obtained results using 21 defecography exams from 21 different patients indicate that the proposed technique is a promising tool in the diagnosis of pelvic floor disorders and can assist the physician in the diagnostic process.