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Local bone enhancement fuzzy clustering for segmentation of MR trabecular bone images
2009
Medical Physics (Lancaster)
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This article examines an alternative approach to trabecular bone segmentation using partial membership segmentation termed fuzzy C-means clustering incorporating local second order features for bone enhancement ...
The algorithm was compared to fuzzy clustering using the intensity as the only feature ͑I-FCM͒ and a dual thresholding algorithm. ...
Burghardt, Benedict Hyun, and Roland Krug for the image acquisition and ROI definition of the tibia image data. ...
doi:10.1118/1.3264615
pmid:20175492
pmcid:PMC2804381
fatcat:poqbnkej55bmjkndulga3kijjy
Automated osteosclerosis grading of clinical biopsies using infrared spectroscopic imaging
[article]
2019
bioRxiv
pre-print
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These disorders result in excess growth of trabecular bone and collagen fibers that replace hematopoietic cells, resulting in abnormal bone marrow function. ...
Treatments using imatinib and JAK2 pathway inhibitors can be effective on osteosclerosis and fibrosis, therefore accurate grading is critical for tracking treatment effectiveness. ...
An average spacing metric describing regularity in trabecular bone spacing was calculated using a distance transform on segmented trabecular bone. ...
doi:10.1101/692434
fatcat:ut75fz3a7bai3eeou7sspio5zm
Automated skeletal tissue quantification in the lower leg using peripheral quantitative computed tomography
2018
Physiological Measurement
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Approach: We employed implicit active contour models and clustering techniques for automated segmentation and identification of bone, muscle and fat at 4%, 38%, and 66% tibia length. ...
Quantification of bone properties is crucial for estimating bone structure resistance to mechanical stress and adaptations to loading. ...
We thank Rahul Patel for performing semi-manual tissue delineations and Fabrizio Lauretani for providing information about the clinical design, instrumentation, and data. ...
doi:10.1088/1361-6579/aaafb5
pmid:29451497
pmcid:PMC5933065
fatcat:vracjzohnjdedpckq5jhq4uh7y
Can the presence of subchondral cyst – An indicator of subchondral bone disturbance, be used for subtyping knee osteoarthritis?
2015
Osteoarthritis and Cartilage
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These bones are, rather than lining on top of existing trabecular bones, clustered in the marrow space normally occupied by the marrow; although it is not yet clear whether these bones of poor quality ...
Subchondral bones with SBCs tend to be of lower BMD, have higher trabecular number and smaller spaces between trabeculae. ...
These bones are, rather than lining on top of existing trabecular bones, clustered in the marrow space normally occupied by the marrow; although it is not yet clear whether these bones of poor quality ...
doi:10.1016/j.joca.2015.02.432
fatcat:ycy5xpiwwbal3ptrmwmyw3ocmu
Radiomics and artificial intelligence analysis of CT data for the identification of prognostic features in multiple myeloma
[article]
2020
arXiv
pre-print
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Preliminary results show that MM is associated to an extension of the intrabone volume for the whole body and that machine learning can identify CT image features mostly correlating with the disease evolution ...
Multiple Myeloma (MM) is a blood cancer implying bone marrow involvement, renal damages and osteolytic lesions. ...
These algorithms utilize pattern recognition in whole-body CT images of patients to segment the compact bone tissue from the bone marrow hosting intrabone volume. ...
arXiv:2001.08924v1
fatcat:4vcsoskffzeprbttcego7ywd74
Hip osteoarthritis: A novel network analysis of subchondral trabecular bone structures
[article]
2022
bioRxiv
pre-print
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Large-scale automated extraction of the network formed by trabecular bone revealed significant network properties not previously reported for bone. ...
We describe a novel network analysis methodology for micro-computed tomography (micro-CT) images of human trabecular bone. ...
The authors wish to acknowledge support from Adelaide Microscopy at the University of Adelaide and Dr Agatha Labrinidis for assisting with micro-CT scanning protocol. ...
doi:10.1101/2022.03.28.486155
fatcat:yt4rtgatcrgbxf44vzx536nz2q
Unique Suites of Trabecular Bone Features Characterize Locomotor Behavior in Human and Non-Human Anthropoid Primates
2012
PLoS ONE
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This study assesses the relationship between inferred locomotor activity and a suite of trabecular bone structural features that characterize bone architecture. ...
Unfortunately, assessments of the correspondence between individual trabecular bone features and inferred behavior patterns have failed to reveal a strong locomotionspecific signal. ...
their assistance with specimens and their willingness to loan specimens for scanning. ...
doi:10.1371/journal.pone.0041037
pmid:22815902
pmcid:PMC3399801
fatcat:iz4atyroavbfxggcsmb7znvc3i
Image processing for the non-destructive characterization of porous media. Application to limestones and trabecular bones
2014
Mathematics and Computers in Simulation
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Different image processing techniques have recently been investigated for the characterization of complex porous media, such as bones, stones and soils. ...
In this paper, we present a series of 3D skeleton-based image processing techniques for evaluating the microarchitecture of large scale disordered porous media. ...
. : Mean ± standard deviation and the Student |t| values for different features estimated from 10 samples of trabecular bone data. ...
doi:10.1016/j.matcom.2013.07.003
fatcat:f2qqjso56fbx7d3ymk5fu4qwia
Influence of the lateral pterygoid muscle on traumatic temporomandibular joint bony ankylosis
2016
BMC Oral Health
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Spiral CT and micro-CT demonstrated that, compared to the experimental group, the control group showed calcified callus formation in the joint space and roughened articular surfaces after new bone formation ...
, which protruded into the joint space. ...
Acknowledgements The authors wish to thank Yang Xue, Xiang-Zhao Sun and Jing-Juan Wang for their valuable assistance in administering the CT
Funding This work was supported by the National Natural ...
doi:10.1186/s12903-016-0220-1
pmid:27234304
pmcid:PMC4884350
fatcat:wihehbxntrbovewhol3b7qh7ie
A Survey of Diagnosis of Dental Image Diseases using Soft Computing Techniques
2021
International Journal for Research in Applied Science and Engineering Technology
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Root Infection is the cause for the Dental cysts and tooth get affected by carious decay. There are mainly three types of Dental cyst i.e. ...
[39] in their paper "Trabecular Texture Analysis in Dental CBCT by Multi-ROI multi feature fusion" explained multi feature multi ROI approach inside oral cavity for analyzing trabecular patterns by ...
The features include the statistical measures of color space, grayscale image ,wavelet transform, Fourier transform. ...
doi:10.22214/ijraset.2021.34070
fatcat:lydbtibunvd7livz4ut53ghlhu
Computer-based automatic classification of trabecular bone pattern can assist radiographic bone quality assessment at dental implant site
2018
British Journal of Radiology
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Volumes-ofinterest comprising only the trabecular bone of the posterior regions were selected and segmented for three-dimensional morphometric parameters calculation. ...
Sparse bone may hamper primary stability, 25 while compact bone with reduction of trabecular spaces may show impaired vascularization. 26 The ideal bone for implant placement lies somewhere in between ...
doi:10.1259/bjr.20180437
pmid:30175923
fatcat:5fg4ktfzrvgtldnbfr6bzamrmi
Comparison of two interpolation methods for empirical mode decomposition based evaluation of radiographic femur bone images
2013
Acta of Bioengineering and Biomechanics
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The trabecular bone regions of normal and osteoporotic femur bone images (N = 40) recorded under standard condition are used for this study. ...
In this work, two interpolation methods of bi-dimensional empirical mode decomposition are analyzed to characterize the trabecular femur bone architecture of radiographic images. ...
The trabecular patterns are distinct and are closely arranged in normal images. In abnormal samples, trabecular spacing is large with high discontinuities. ...
pmid:23952640
fatcat:qofpmvlglrhn5kkqn5hdn5fmg4
Mapping trabecular disconnection "hotspots" in aged human spine and hip
2015
Bone
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Trabecular bone disconnection is an independent factor in age-related skeletal failure where real termini (ReTm; rare in youth) may cause weakness disproportionate to tissue loss, yet their structural ...
Comparative experimentation by marrow elution of an OP animal model demonstrated "floating segments" as a possible outcome. ...
Acknowledgments JEA, LDH and PAS are grateful to Action Medical Research and the HSA Charitable Trust for sequential project support for nine years on this and interrelated aspects. ...
doi:10.1016/j.bone.2015.04.009
pmid:25874446
fatcat:krtf5n67ineafn4omrxvy5xivq
High-Resolution Imaging Techniques for the Assessment of Osteoporosis
2010
The Radiologic clinics of North America
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In addition Multidetector-CT has been used for high-resolution imaging of trabecular bone structure, however, the radiation dose is a limiting factor. ...
Details regarding imaging protocols as well as image post-processing methods for bone structure quantification are discussed. ...
Carballido-Gamio et al. (44) used fuzzy clustering for trabecular bone segmentation and to evaluate BV/TV measurements. ...
doi:10.1016/j.rcl.2010.02.015
pmid:20609895
pmcid:PMC2901255
fatcat:fz2mbtlssjcq7kvbxyu5pre4yi
Change in bone area does not correlate with cartilage loss over 12 months in individuals with knee OA: Data from the osteoarthritis initiative
2015
Osteoarthritis and Cartilage
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Baseline and 12-month DESS images were manually segmented for articular cartilage. Segmenters were blinded to time point but not to subject, using EndPoint software (Imorphics, UK). ...
Bone surfaces were identified by automated segmentation using active appearance models (AAMs). ...
These bones are, rather than lining on top of existing trabecular bones, clustered in the marrow space normally occupied by the marrow; although it is not yet clear whether these bones of poor quality ...
doi:10.1016/j.joca.2015.02.431
fatcat:sp2njitqgvht5ijiqf3tmuxxca
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