Automatic determination of the newborn's femoral head from three-dimensional ultrasound image data

Overhoff, Heinrich Martin; Lazovic, Djordje; Franke, Jörg; Jan, Ute von

doi:10.1007/bfb0029278

Cited by 6 publications

(8 citation statements)

References 4 publications

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“…[9]). The figure underlines the correct choice of the thresholds in [7], as for the ranges 1).8 < 11 (gTHRES,SKELETON) < 0.95 and 0.85 < tt (gTHRES,CONTOUR) < 0.95 significantly high correctness can be gained.…”

Section: Resultsmentioning

confidence: 68%

“…An automatic image analysis for the femoral head approximation [7] was extended by an algorithm identifying the acetabular landmarks (2) and (3). The entire procedure is described in the following.…”

Section: Methodsmentioning

confidence: 99%

“…The diameter-range of the "C" was chosen to 20 < D / pixel < 60, as D --40pixel is a typical femoral head radius (cf. [7]). Its centre is taken as provisional centre of the femoral head approximating sphere.…”

Section: Methodsmentioning

confidence: 99%

“…For details cf. [7]. The result of the sphere detection is a parameter vector [Xcentre Y centre z centre D].…”

Section: Methodsmentioning

confidence: 99%

“…the derivation of geometric measures of the joint based on a spatial representation, to our knowledge has not been reported so far (cf. [7]). …”

Section: Introductionmentioning

confidence: 99%

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Computer-based determination of the newborn’s femoral head coverage using three-dimensional ultrasound scans

Overhoff

Heinze

Lazovic

et al. 1998

Medical Image Computing and Computer-Assisted Intervention — MICCAI’98

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Abstract. An automatic image analysis method is presented, which finds the diagnostic landmarks for the determination of the femoral head coverage according to Graf's method in a 3-D ultrasound image volume. Some of the process steps depend on tuneable parameters. It is a typical experience that the quality of images differs between investigators and patients respectively. An image analysis algorithm therefore should produce results which are robust against such varying image quality. The sensitivity of intermediary and final image analysis process steps versus expert defined parameters is investigated. This analysis are performed in a pilot study on 3-D image data of 10 newborns.

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Section: Resultsmentioning

confidence: 68%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…For details cf. [7]. The result of the sphere detection is a parameter vector [Xcentre Y centre z centre D].…”

Section: Methodsmentioning

confidence: 99%

“…the derivation of geometric measures of the joint based on a spatial representation, to our knowledge has not been reported so far (cf. [7]). …”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Computer-based determination of the newborn’s femoral head coverage using three-dimensional ultrasound scans

Overhoff

Heinze

Lazovic

et al. 1998

Medical Image Computing and Computer-Assisted Intervention — MICCAI’98

Self Cite

View full text Add to dashboard Cite

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Parametric 3D Hip Joint Segmentation for the Diagnosis of Developmental Dysplasia

Luis‐García

Alberola-López

2006

2006 International Conference of the IEEE Engineering in Medicine and Biology Society

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In this paper, we present a segmentation method for the hip joint from 3D ultrasound data. The proposed approach starts from a well-known energy formulation of the segmentation problem, and employs the extended local structure tensor as image feature in order to incorporate gray level and texture information in a common framework. Using the Kullback-Leibler distance as an intrinsic dissimilarity measure, the energy minimization is performed by estimating the optimal parameters of the shpere and paraboloid that best approximate the femoral head and acetabulum, respectively. A 2D level set segmentation of the iliac bone and an easy user interaction step allow for the introduction of the necessary constraints to make the energy minimization feasible. Experimental results over several data volumes show this approach to be capable of successfully approximating the anatomy of the hip joint by simple geometrical surfaces.

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<title>Reliable identification of sphere-shaped femoral heads in 3D image data</title>

1999

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Automatic determination of the newborn's femoral head from three-dimensional ultrasound image data

Cited by 6 publications

References 4 publications

Computer-based determination of the newborn’s femoral head coverage using three-dimensional ultrasound scans

Computer-based determination of the newborn’s femoral head coverage using three-dimensional ultrasound scans

Parametric 3D Hip Joint Segmentation for the Diagnosis of Developmental Dysplasia

<title>Reliable identification of sphere-shaped femoral heads in 3D image data</title>

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