Global point signature for shape analysis of carpal bones

Chaudhari, Abhijit J.; Leahy, Richard M.; Lane, Nancy E.; Badawi, Ramsey D.; Joshi, Anand A.

doi:10.1088/0031-9155/59/4/961

Cited by 31 publications

(20 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method provided a local metric for shape comparison in Euclidean space as opposed to a global metric [33] or a metric in a different space [29]. A comparison of RBM with these other techniques will be carried out in the future.…”

Section: Discussionmentioning

confidence: 99%

“…Further, these approaches were not tested for enabling quantitative comparisons based on carpal bone shape between populations. We proposed an approach for shape analysis of the individual carpal bones based on the global point signature (GPS) metric [33]. In this method an individual carpal bone shape was parameterized based on the eigen system of the Laplace-Beltrami operator.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist

Joshi

Leahy

Badawi

et al. 2016

IEEE Trans. Med. Imaging

View full text Add to dashboard Cite

We present a method that quantifies point-wise changes in surface morphology of the bones of the human wrist. The proposed method, referred to as Registration-based Bone Morphometry (RBM), consists of two steps: an atlas selection step and an atlas warping step. The atlas for individual wrist bones was selected based on the shortest l2 distance to the ensemble of wrist bones from a database of a healthy population of subjects. The selected atlas was then warped to the corresponding bones of individuals in the population using a non-linear registration method based on regularized l2 distance minimization. The displacement field thus calculated showed local differences in bone shape that then were used for the analysis of group differences. Our results indicate that RBM has potential to provide a standardized approach to shape analysis of bones of the human wrist. We demonstrate the performance of RBM for examining group differences in wrist bone shapes based on sex and between those of the right and left wrists in healthy individuals. We also present data to show the application of RBM for tracking bone erosion status in rheumatoid arthritis.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist

Joshi

Leahy

Badawi

et al. 2016

IEEE Trans. Med. Imaging

View full text Add to dashboard Cite

show abstract

“…Please see Table 2 for the measures by carpal bone for the healthy participants and Table 3 for the measures by carpal bone for the OA participants. In general, the proposed method provided smoother segmentations than the individual observers (Figure 9), which may be important for bone shape analysis [3, 19]. Please see Figure 10 which shows segmentation examples from the proposed method on a less noisy and noisy MRI scans.…”

Section: Resultsmentioning

confidence: 99%

WRIST: A WRist Image Segmentation Toolkit for carpal bone delineation from MRI

Foster

Joshi

Borgese

et al. 2018

Computerized Medical Imaging and Graphics

View full text Add to dashboard Cite

Segmentation of the carpal bones from 3D imaging modalities, such as magnetic resonance imaging (MRI), is commonly performed for in vivo analysis of wrist morphology, kinematics, and biomechanics. This crucial task is typically carried out manually and is labor intensive, time consuming, subject to high inter- and intra-observer variability, and may result in topologically incorrect surfaces. We present a method, WRist Image Segmentation Toolkit (WRIST), for 3D semi-automated, rapid segmentation of the carpal bones of the wrist from MRI. In our method, the boundary of the bones were iteratively found using prior known anatomical constraints and a shape-detection level set. The parameters of the method were optimized using a training dataset of 48 manually segmented carpal bones and evaluated on 112 carpal bones which included both healthy participants without known wrist conditions and participants with thumb basilar osteoarthritis (OA). Manual segmentation by two expert human observers was considered as a reference. On the healthy subject dataset we obtained a Dice overlap of 93.0 ± 3.8, Jaccard Index of 87.3 ± 6.2, and a Hausdorff distance of 2.7 ± 3.4 mm, while on the OA dataset we obtained a Dice overlap of 90.7 ± 8.6, Jaccard Index of 83.0 ± 10.6, and a Hausdorff distance of 4.0 ± 4.4 mm. The short computational time of 20.8 s per bone (or 5.1 s per bone in the parallelized version) and the high agreement with the expert observers gives WRIST the potential to be utilized in musculoskeletal research.

show abstract

“…Baseline Methods For each of the 3D shape benchmarks used for experimentation, we will report the comparison results of GraphBDM against various state-of-the-art methods, including shape-DNA [1], compact shape-DNA [11], GPS embedding [9], and F1-, F2-, and F3-features [37]. The latter features, which are defined in terms of the Laplacian matrix eigenvalues, were shown to have good inter-class discrimination capabilities in 2D shape recognition [11], but they can easily be extended to 3D shape analysis using the eigenvalues of the LBO.…”

Section: Resultsmentioning

confidence: 99%

A graph-theoretic approach to 3D shape classification

Hamza

2016

Neurocomputing

View full text Add to dashboard Cite

Global point signature for shape analysis of carpal bones

Cited by 31 publications

References 49 publications

Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist

Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist

WRIST: A WRist Image Segmentation Toolkit for carpal bone delineation from MRI

A graph-theoretic approach to 3D shape classification

Contact Info

Product

Resources

About