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Fully automated quantitative cephalometry using convolutional neural networks
2017
Journal of Medical Imaging
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We use a publicly available cephalometric x-ray image dataset to train CNNs for recognition of landmark appearance patterns. ...
Overall, our results demonstrate high anatomical landmark detection accuracy (∼1% to 2% higher success detection rate for a 2-mm range compared with the top benchmarks in the literature) and high anatomical ...
Yue et al. 2 combined statistical gray-level image patches with a principal component analysis-based shape model for cephalometric landmark detection. ...
doi:10.1117/1.jmi.4.1.014501
pmid:28097213
pmcid:PMC5220585
fatcat:k256yfxbdbcunnqpcg2db4dasi
A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings
2019
Sensors
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We implement methods for face detection, facial landmark detection, face frontalization and analysis, combining all of these into a fully automated workflow. ...
We present a system that utilizes a range of image processing algorithms to allow fully automated thermal face analysis under both laboratory and real-world conditions. ...
Facial Landmark Detection The landmark detection subtask is crucial for the performance of the whole pipeline since accurately detected landmarks are a key requirement for further processing. ...
doi:10.3390/s19194135
pmid:31554260
pmcid:PMC6806182
fatcat:ehxc4ddf6ndwrejyrkkp7ju2gi
Automated down syndrome detection using facial photographs
2013
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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Then geometric features and texture features based on local binary patterns are extracted around each landmark. Finally, Down syndrome is detected using a variety of classifiers. ...
In this study, we propose a novel strategy based on machine learning techniques to detect Down syndrome automatically. A modified constrained local model is used to locate facial landmarks. ...
Photography and image analysis could serve as a readily available and powerful tool for automated computer-aided diagnosis of Down syndrome. ...
doi:10.1109/embc.2013.6610339
pmid:24110526
dblp:conf/embc/ZhaoROZSSL13
fatcat:k7rawzjzx5dr7ftuxn3y24uxgq
Automatic identification of landmarks in digital images
2010
IET Computer Vision
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They are widely used in shape analysis and a typical shape analysis study involves several hundred digital images. ...
The authors present an automated system for feature recognition in digital images. Morphometric landmarks are points that can be defined in all specimens and located precisely. ...
This framework of shape analysis by landmarks is increasingly used in many biological and medical applications and is widely applied in many other fields. ...
doi:10.1049/iet-cvi.2009.0014
fatcat:umd3vql3yfholnkbkm2ihos4y4
The accuracy of a designed software for automated localization of craniofacial landmarks on CBCT images
2014
BMC Medical Imaging
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However, manual landmark detection depends on medical expertise, and the process is time-consuming. ...
The differences in the distances of coordinates of each landmark on each image between manual and automated detection methods were calculated and reported as mean errors. ...
Vosough of the Center of Research Improvement of the School of Dentistry for the statistical analysis.
Author details ...
doi:10.1186/1471-2342-14-32
pmid:25223399
pmcid:PMC4171715
fatcat:dj2o5uyzajdodmpzvqbyoctt5y
Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses
2015
2015 IEEE 28th International Symposium on Computer-Based Medical Systems
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The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. ...
Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens ...
ACKNOWLEDGMENT We would like to thank Sara Finkleman for helping with landmark collection and Dr. Sara Rolfe and Dr. Murat Maga for general technical guidance and valuable feedback on the manuscript. ...
doi:10.1109/cbms.2015.86
pmid:26258171
pmcid:PMC4526271
dblp:conf/cbms/AnejaVCSC15
fatcat:xbruibgr6vdztpa5qyozjahpie
Craniofacial Image Analysis
[chapter]
2015
Health Monitoring and Personalized Feedback using Multimedia Data
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Using advanced computer vision and image analysis techniques, diagnosis and quantification of craniofacial syndromes can be improved and automated. ...
Craniofacial researchers have used anthropometric measurements taken directly on the human face for research and medical practice for decades. ...
Computer vision and image analysis techniques are being used for enhancing images, detecting anomalies, visualizing data in different dimensions and guiding medical experts. ...
doi:10.1007/978-3-319-17963-6_2
fatcat:knbkjazuqzhlrktu3bm6cjtq6y
State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods
2021
Diagnostics
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Geometric morphometric analysis is the statistical analysis of the patterns of shape change of an anatomical structure. ...
Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. ...
These include convolutional neural networks (CNNs) that have been extensively applied to medicine, especially for medical image processing. ...
doi:10.3390/diagnostics11091545
pmid:34573887
pmcid:PMC8470585
fatcat:ezsoxoma4jgznoqgazsathm4qa
Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis
[article]
2021
arXiv
pre-print
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Building a machine learning based automated analysis is necessary to extract the additional imaging information necessary for expanding original manual analyses. ...
A U-Net architecture was used for detection of the endocardial and epicardial boundaries in short axis images. ...
Acknowledgments We would like to thank Benjamin Wen and Augustin Okamura for their analysis of the data. ...
arXiv:2110.15144v1
fatcat:5gmbihjrgjhn3f73hb734z7ik4
A hierarchical method based on active shape models and directed Hough transform for segmentation of noisy biomedical images; application in segmentation of pelvic X-ray images
2009
BMC Medical Informatics and Decision Making
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Automated fracture detection from initial patient X-ray images can assist physicians in rapid diagnosis and treatment, and a first and crucial step of such a method is to segment key bone structures within ...
An error measures is calculated based on the shapes detected with each method and the gold standard shapes. ...
The authors would also like to thank Scott Smith for his valuable feedback and discussion on this work. ...
doi:10.1186/1472-6947-9-s1-s2
pmid:19891796
pmcid:PMC2773917
fatcat:fjb25b557nazrdq4wmfe2ashna
A benchmark for comparison of dental radiography analysis algorithms
2016
Medical Image Analysis
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Radiography Caries Detection Challenge and Cephalometric X-ray Image Analysis Challenge. ...
In recent years, efforts have been made on developing computerized dental X-ray image analysis systems for clinical usages. ...
detection in cephalometric radiographs
• Challenge 1: Automated detection and analysis for diagnosis in cephalometric x-ray image
• Task1: landmark detection (similar to 2014)
• Task2: classification ...
doi:10.1016/j.media.2016.02.004
pmid:26974042
fatcat:zh6jbp3vdvavjc6dek5q7ngnw4
Automatic landmarking of cephalograms using active appearance models
2010
European Journal of Orthodontics
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Acknowledgement The authors are grateful to Professor Tim Cootes, Division of Imaging Science and Biomedical Engineering, University of Manchester, UK, for providing the open C++ source code set of AAM ...
tools for this research and for his kind help. ...
The image plate was processed by a PCTDigora medical image laser scanner (Soredex). ...
doi:10.1093/ejo/cjp099
pmid:20203126
fatcat:43pu7dxeebhijpfd2o652cfwam
Automated Detection of Regional Wall Motion Abnormalities Based on a Statistical Model Applied to Multislice Short-Axis Cardiac MR Images
2009
IEEE Transactions on Medical Imaging
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In this paper, a statistical shape analysis method for myocardial contraction is presented that was built to detect and locate regional wall motion abnormalities (RWMA). ...
Index Terms-Independent component analysis (ICA), medical diagnosis, pattern classification, regional wall motion abnormality (RWMA), statistical shape analysis. ...
The sparseness characteristic of ICA has been exploited for an automated detection of tissue disorders in 3-D aortic vessels [21] and for image segmentation [22] . ...
doi:10.1109/tmi.2008.2008966
pmid:19211347
fatcat:qr6o62lea5g6fglcmwzgqpbtgu
Model Constructions for Computational Anatomy
計算解剖モデルの構築
2013
Medical Imaging Technology
計算解剖モデルの構築
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of medical image sciences" (http://www.comp-anatomy.org/) funded by Grant-in-Aid for Scientific Research on Innovative Areas, MEXT, Japan. ...
recognizing the anatomical structures and analyzing the functions of different organs in a whole body region, all of which are imaged with imaging modalities such as CT, MR, PET, eye fundus photograph ...
Acknowledgments Authors thank to many members in our Laboratory for their collaboration and advices. ...
doi:10.11409/mit.31.278
fatcat:lokkx2pglnfave4bwbqblogl74
Robust automated constellation-based landmark detection in human brain imaging
2018
NeuroImage
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A robust fully automated algorithm for identifying an arbitrary number of landmark points in the human brain is described and validated. ...
This estimation model sequentially uses the knowledge of each additional detected landmark as an improved foundation for improved prediction of the next landmark location. ...
Acknowledgments This research was supported by NIH Neurobiological Predictors of Huntington's Disease (PREDICT-HD; NS40068, NS050568), National Alliance for Medical Image Computing (NAMIC; EB005149 / Brigham ...
doi:10.1016/j.neuroimage.2017.04.012
pmid:28392490
pmcid:PMC5630513
fatcat:n6dkg6dmffeotkpru7zy3atgly
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