Pelvic anatomy and MRI

Paramasivam, Srinivasan; Proietto, Anthony; Puvaneswary, M

doi:10.1016/j.bpobgyn.2005.09.001

Cited by 20 publications

(11 citation statements)

References 15 publications

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“…A thickness of 1 mm is assumed as the minimum tolerance of the bladder wall thickness based on the reports. 10,18 The value 1/r maps the minimal thickness to the Euclidean point distance on the image. The irregularity of the inner boundary also affects the field; the larger the curvature is, the higher the possibility for the moving contour to deform is.…”

Section: Segmentation Of the Outer Boundarymentioning

confidence: 99%

“…3,6,13,14,20 Successful applications of MRI to detect bladder-related conditions have been reported in many articles in the literature. 2,7,11,18 T1-and T2-weighted MRI are two basic scans for imaging the bladder, where T1 is the spin-lattice relaxation time and T2 is the spin-spin lattice relaxation time. Different tissues have distinct T1 and T2 values, and the difference can be detected under an electromagnetic field by applying specific pulse sequences.…”

Section: Introductionmentioning

confidence: 99%

“…The normal bladder wall is thin and smooth with a thickness of around 2 mm when moderately distended. 18 Various imaging modalities have been used to visualize the bladder. Cystoscopy is the conventional way to monitor the bladder but it is painful for the patients and only the inner bladder surface can be observed.…”

Section: Introductionmentioning

confidence: 99%

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Novel Approach to Segment the Inner and Outer Boundaries of the Bladder Wall in T2-Weighted Magnetic Resonance Images

Jorge

Mascarenhas

et al. 2011

Ann Biomed Eng

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Diagnosis of bladder-related conditions needs critical measurements which require the segmentation of the inner and outer boundaries of the bladder wall. In T2-weighted MR images, the low-signal intensity bladder wall can be identified due to the large contrast with the high-signal intensity urine and perivesical fat. In this article, two deformable models are proposed to segment the bladder wall. Based on the imaging features of the bladder, a modified geodesic active contour is proposed to segment the inner boundary. This method uses the statistical information of the bladder lumen and can handle the intensity variation in MR images. Having obtained the inner boundary, a shape influence field is formed and integrated with the Chan-Vese (C-V) model to segment the outer boundary. The shape-guided C-V model can prevent the overlapping between the two boundaries when the appearance of the bladder wall is blurred. Segmentation examples are presented and analyzed to demonstrate the effectiveness of this novel approach.

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Section: Segmentation Of the Outer Boundarymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Novel Approach to Segment the Inner and Outer Boundaries of the Bladder Wall in T2-Weighted Magnetic Resonance Images

Jorge

Mascarenhas

et al. 2011

Ann Biomed Eng

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“…Common symptoms include urinary incontinence, fecal incontinence, pelvic organ prolapse, etc. Many works including biomechanical simulations and clinical studies have been carried out to reveal the causes of these symptoms ; in such studies, imaging techniques have an important role.…”

Section: Introductionmentioning

confidence: 99%

“…The detection of pathology relies on a clear visualization of the soft tissues . Magnetic resonance (MR) imaging is preferred in many studies because of its superior imaging quality of soft tissues, and MR images have been of noteworthy assistance in clinical diagnoses.…”

Section: Introductionmentioning

confidence: 99%

Segmentation of female pelvic cavity in axial T2‐weighted MR images towards the 3D reconstruction

Jorge

Mascarenhas

et al. 2012

Numer Methods Biomed Eng

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The anatomies of pelvic structures are critical for the diagnosis of pelvic floor dysfunctions. However, because of the complex background, the imaging appearances of pelvic organs and muscles are frequently distorted by noise and partial volume effect. Magnetic resonance imaging with its clear imaging quality of the female pelvic cavity is preferred for many studies. As such, correct segmentations of the pelvic structures on MR images are required for accurate diagnoses. Effective algorithms for axial T2-weighted MR images have been proposed, which are based on the imaging features of different structures and various image clues. In this paper, we review these algorithms and evaluate their performance, and discuss implementation issues and aspects towards constructing the three-dimensional models.

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