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A novel method to automatically segment the pelvic floor muscles in MR images

The high prevalence of pelvic floor disorders has raised increasing attentions on the study of pelvic cavity [1]. Thanks to the advances of imaging techniques doctors can obtain high resolution images of the pelvic cavity which considerably enhanced the accuracy of diagnosis. The usual first step of medical image processing is to segment the organs and structures presented in the image slices, among which a correct segmentation of pelvic floor muscles is crucial for the later 3D reconstruction and analysis. However, along with the changes of positions and viewpoints the appearances of pelvic floor muscles have large shape variations. Meanwhile these muscles are usually surrounded by fiber structures and are highly textured so that they have a poor resolution in the images acquired. All these factors make a correct segmentation hard to perform even when done manually by a well qualified technician. Given the considerations of improving the time efficiency, robustness and decreasing the intra-observer or inter-observer errors, an effective computer-aided algorithm is urgently needed. In this paper, magnetic resonance imaging (MRI) is chosen as the imaging modality of study, because MR images have better views of soft tissues when compared with other noninvasive modalities, and a novel method to automatically segment the pelvic muscles is proposed.