Automated identification of anatomical landmarks on 3D bone models reconstructed from CT scan images

Subburaj, Karupppasamy; Ravi, B.; Agarwal, Manish

doi:10.1016/j.compmedimag.2009.03.001

Cited by 85 publications

(72 citation statements)

References 25 publications

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“…The remaining three points correspond to specific anatomical landmarks, which need to be defined in order to match the SSMs to the radiographic scene. These landmarks are commonly used in literature [21], [22], [23] and are depicted in Fig. 1.…”

Section: D/3d Reconstructionmentioning

confidence: 99%

Radiographic reconstruction of lower-extremity bone fragments: a first trial

et al. 2016

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Purpose The correct rotational alignment of a fractured long bone is an important step in the fracture reduction process. In order to plan the fracture reduction and the appropriate external fixation, plain radiographs are conventionally used. But as three-dimensional information of the complex situation is not available, the correct amount of rotation can only be approximated. Thus, the objective of this study is to develop a system to assess the rotational relationship between proximal and distal fragments of the tibia and femur based on a set of two calibrated X-ray radiographs.Methods In order to robustly determine the rotational alignment of proximal and distal bone fragments, a 2D/3D reconstruction approach was employed to reconstruct the fractured bone fragments. Two different studies were performed to evaluate the accuracy of the complete system for the purpose of fracture reduction.Results The reconstruction accuracy was evaluated in terms of major bone axis and in-plane rotational alignment. The long bone axis of the femur and tibia could be derived an average with an error of 0.33 ± 0.27 • , while an average inplane rotational error of 2.27 ± 1.76 • and 2.67 ± 1.80 • was found for the proximal and distal fragment, respectively. The overall mean surface reconstruction error of tibial fragments was 0.81 ± 0.59 mm and 1.12 ± 0.87 mm for femoral fragments.Conclusions A new approach for estimating the rotational parameters of fractured bone fragments has been proposed. This approach is based on two conventional radiographs and 2D/3D reconstruction technology. It is generally applicable to the reduction of any simple long bone fracture and could provide an important means for external fracture fixations.

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Section: D/3d Reconstructionmentioning

confidence: 99%

Radiographic reconstruction of lower-extremity bone fragments: a first trial

et al. 2016

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“…Therefore, intra-and interobserver variability is an important factor that should be taken into account when using landmark-based clinical parameters. Several studies have been performed to assess the reproducibility of landmark identification on CT or MR (-based) images and the corresponding morphological parameters (Cerveri et al 2010, Lerner et al 2003, Nofrini et al 2004, Subburaj et al 2009, Victor et al 2009, Yoshino et al 2001), see Table 1. A direct comparison between studies is not feasible, because of the different methods that are used, but their results indicate that mean variabilities of 2-3 mm/° are not uncommon for some of the landmarks and parameters.…”

Section: Virtual Landmark Identificationmentioning

confidence: 99%

Patient-Specific Modelling in Orthopedics: From Image to Surgery

Gomes

Cauter

Beule

et al. 2012

Biomedical Imaging and Computational Modeling in Biomechanics

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In orthopedic surgery, to decide upon intervention and how it can be optimized, surgeons usually rely on subjective analysis of medical images of the patient, obtained from computed tomography, magnetic resonance imaging, ultrasound or other techniques. Recent advancements in computational performance, image analysis and in silico modeling techniques have started to revolutionize clinical practice through the development of quantitative tools, including patient-specific models aiming at improving clinical diagnosis and surgical treatment. Anatomical and surgical landmarks as well as features extraction can be automated allowing for the creation of general or patient-specific models based on statistical shape models. Preoperative virtual planning and rapid prototyping tools allow the implementation of customized surgical solutions in real clinical environments. In the present chapter we discuss the applications of some of these techniques in orthopedics and present new computer-aided tools that can take us from image analysis to customized surgical treatment.

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“…For such reasons, surface curvature has been widely proposed as a shape descriptor and investigated for the automatic extraction of MCL. It has been applied to the analysis of patterns of cranial morphological differentiation in rodent species [30] and for MCL detection in femur and pelvic bone models [29,31]. However, in using surface curvature to detect MCL in bone shapes, two main issues have to be addressed.…”

Section: Introductionmentioning

confidence: 99%

“…Tel: þ39-0223993352. E-mail: pietro.cerveri@polimi.it surface regions based on their appearance and shape [16,[26][27][28][29]. Specifically, the surface curvature is an invariant, independent of position and orientation, that can be exploited for reliable detection of geometric features as concavities and convexities.…”

Section: Introductionmentioning

confidence: 99%

“…Statistical models of bone structures have been investigated extensively with the aim of enhancing automation in CT and MR image segmentation [6][7][8][9][10][11][12] and reconstructing patientspecific shape models from a small number of X-ray images or even from a single image [13][14][15]. Innovative methods for bone shape analysis have been applied to 3D mesh segmentation and clinical feature detection [16][17][18][19][20][21]. In this domain, automatic shape analysis is strongly advocated because it offers the opportunity to detect morphological and clinical landmarks (MCL) with superior repeatability in comparison to human operators.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mean-shifted surface curvature algorithm for automatic bone shape segmentation in orthopedic surgery planning: a sensitivity analysis

Cerveri

Manzotti

Marchente

et al. 2012

Computer Aided Surgery

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The results of recent studies concerning statistical bone atlases and automated shape analysis are promising with a view to widening the use of surface models in orthopedic clinical practice, both in pre-operative planning and in the intra-operative stages. In this domain, automatic shape analysis is strongly advocated because it offers the opportunity to detect morphological and clinical landmarks with superior repeatability in comparison to human operators. Surface curvatures have been proposed extensively for segmentation and labeling of image and surface regions based on their appearance and shape. The surface curvature is an invariant that can be exploited for reliable detection of geometric features. In this paper, we investigate the potentiality of the algorithm termed mean-shift (MS), as applied to a non-linear combination of the minimum and maximum curvatures of a surface. We exploited a sensitivity analysis of the algorithm parameters across increasing surface resolutions. Results obtained with femur and pelvic bone surface data, reconstructed from cadaveric CT scans, demonstrated that the information content derived by the MS non-linear curvature overcomes both the mean and the Gaussian curvatures and the original non-linear curvature. By applying a threshold-based clustering algorithm to the curvature distribution, we found that the number of clusters yielded by the MS non-linear curvature is significantly lower (by a factor of up to 6) than that obtained by using the original non-linear curvature. In conclusion, this study provides valuable insights into the use of surface curvature for automatic shape analysis.

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Automated identification of anatomical landmarks on 3D bone models reconstructed from CT scan images

Cited by 85 publications

References 25 publications

Radiographic reconstruction of lower-extremity bone fragments: a first trial

Radiographic reconstruction of lower-extremity bone fragments: a first trial

Patient-Specific Modelling in Orthopedics: From Image to Surgery

Mean-shifted surface curvature algorithm for automatic bone shape segmentation in orthopedic surgery planning: a sensitivity analysis

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