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Analysis Of Magnetic Resonance Imaging ( Mri ) Based Three Dimensional Reconstruction

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Magnetic Resonance Imaging (MRI) based three dimensional reconstruction has been used successfully to evaluate the female pelvic floor muscles and tissues in women with and without pelvic floor dysfunction [1, 2]. Furthermore, MR based 3D reconstructed models have been used to generate finite-element and element free computational models suitable for simulating vaginal child-birth [3, 4], offering insight into risk factors for childbirth related pelvic floor injury. The Finite Element Method has also been used to evaluate anterior vaginal wall support, and the mechanisms underlying cystocele formation [5]. Precise segmentation of pelvic magnetic resonance images (MRI) is an important step in building the three-dimensional (3D) reconstructed structural models suitable for computational analysis. Segmentation consists of outlining each organ or tissue of interest from the underlying grayscale images on each slice in the dataset.

The 3D reconstructed models are currently generated from manually segmented label-maps, which currently require multiple hours of tedious manual segmentation to produce each reconstructed 3D model. This manual segmentation bottleneck limits the number of computational models that can be reliably produced in a timely manner, thereby limiting the number of study subjects available for the kind of statistical comparisons that can potentially lead to clinically meaningful insight. In addition, the structures of the female pelvic floor are very complex

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