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Fully automated quantitative cephalometry using convolutional neural networks

Sercan Ö. Arik, Bulat Ibragimov, Lei Xing
2017 Journal of Medical Imaging  
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

Marcin Kopaczka, Lukas Breuer, Justus Schock, Dorit Merhof
2019 Sensors  
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

Qian Zhao, Kenneth Rosenbaum, Kazunori Okada, Dina J. Zand, Raymond Sze, Marshall Summar, Marius George Linguraru
2013 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
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

S. Palaniswamy, N.A. Thacker, C.P. Klingenberg
2010 IET Computer Vision  
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

Shoaleh Shahidi, Ehsan Bahrampour, Elham Soltanimehr, Ali Zamani, Morteza Oshagh, Marzieh Moattari, Alireza Mehdizadeh
2014 BMC Medical Imaging  
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

Deepali Aneja, Siddharth R. Vora, Esra D. Camci, Linda G. Shapiro, Timothy C. Cox
2015 2015 IEEE 28th International Symposium on Computer-Based Medical Systems  
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]

Ezgi Mercan, Indriyati Atmosukarto, Jia Wu, Shu Liang, Linda G. Shapiro
2015 Health Monitoring and Personalized Feedback using Multimedia Data  
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

Pichet Ruenchit
2021 Diagnostics  
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]

Avan Suinesiaputra, Charlene A Mauger, Bharath Ambale-Venkatesh, David A Bluemke, Josefine Dam Gade, Kathleen Gilbert, Mark Janse, Line Sofie Hald, Conrad Werkhoven, Colin Wu, Joao A Lima, Alistair A Young
2021 arXiv   pre-print
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

Rebecca Smith, Kayvan Najarian, Kevin Ward
2009 BMC Medical Informatics and Decision Making  
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

Ching-Wei Wang, Cheng-Ta Huang, Jia-Hong Lee, Chung-Hsing Li, Sheng-Wei Chang, Ming-Jhih Siao, Tat-Ming Lai, Bulat Ibragimov, Tomaž Vrtovec, Olaf Ronneberger, Philipp Fischer, Tim F. Cootes (+1 others)
2016 Medical Image Analysis  
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/ pmid:26974042 fatcat:zh6jbp3vdvavjc6dek5q7ngnw4

Automatic landmarking of cephalograms using active appearance models

P. Vucinic, Z. Trpovski, I. Scepan
2010 European Journal of Orthodontics  
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

A. Suinesiaputra, A.F. Frangi, T. Kaandorp, H.J. Lamb, J.J. Bax, J. Reiber, B. Lelieveldt
2009 IEEE Transactions on Medical Imaging  
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

Hiroshi FUJITA, Takeshi HARA, Xiangrong ZHOU, Chisako MURAMATSU, Naoki KAMIYA
2013 Medical Imaging Technology  
of medical image sciences" ( 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

Ali Ghayoor, Jatin G. Vaidya, Hans J. Johnson
2018 NeuroImage  
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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