A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative.

Although recognized as a valuable diagnostic tool for more than 60 years, many laryngologists do not routinely use laryngeal electromyography (LEMG). This may be due to a persisting lack of agreement on methodology, interpretation, validity, and clinical application of LEMG. To achieve consensus in these fields, a laryngeal electromyography working group of European neurolaryngologic experts was formed in order to (1) evaluate guidelines for LEMG performance and (2) identify issues requiring further clarification. To obtain an overview of existing knowledge and research, English-language literature about LEMG was identified using Medline. Additionally, cited works not detected in the initial search were screened. Evidence-based recommendations for the performance and interpretation of LEMG and also for electrostimulation for functional evaluation were considered, as well as published reports based on expert opinion and single-institution retrospective case series. To assess the data obtained by this literature evaluation, the working group met five times and performed LEMG together on more than 20 patients. Subsequently, the results were presented and discussed at the 8th Congress of the European Laryngological Society in Vienna, Austria, September 1–4, 2010, and consensus was achieved in the following areas: (1) minimum requirements for the technical equipment required to perform and record LEMG; (2) best practical implementation of LEMG; (3) criteria for interpreting LEMG. Based on this consensus, prospective trials are planned to improve the quality of evidence guiding the proceedings of practitioners.

Laryngeal electromyography: a proposal for guidelines of the European Laryngological Society

Although recognized as a valuable diagnostic tool for more than 60 years, many laryngologists do not routinely use laryngeal electromyography (LEMG). This may be due to a persisting lack of agreement on method- ology, interpretation, validity, and clinical application of LEMG. To achieve consensus in these fields, a laryngeal electromyography working group of European neurolar- yngologic experts was formed in order to (1) evaluate guidelines for LEMG performance and (2) identify issues requiring further clarification. To obtain an over- view of existing knowledge and research, English-language literature about LEMG was identified using Medline. Additionally, cited works not detected in the initial search were screened. Evidence-based recommendations for the performance and interpretation of LEMG and also for electrostimulation for functional evaluation were consid- ered, as well as published reports based on expert opinion and single-institution retrospective case series. To assess the data obtained by this literature evaluation, the working group met five times and performed LEMG together on more than 20 patients. Subsequently, the results were presented and discussed at the 8th Congress of the Euro- pean Laryngological Society in Vienna, Austria, Septem- ber 1-4, 2010, and consensus was achieved in the following areas: (1) minimum requirements for the tech- nical equipment required to perform and record LEMG; (2)

Laryngeal electromyography: a proposal for guidelines of the European Laryngological Society Gerd Fabian VolkRudolf HagenClaus PototschnigGerhard FriedrichTadeus NawkaChristoph Arens • Andreas MuellerGerhard FoersterMira FinkensieperRuth Lang-RothChristian SittelClaudio Storck • Maria GroshevaM. Nasser KotbyCarsten M. KlingnerOrlando Guntinas-Lichius

Dental biometrics: Human identification based on teeth and dental works in bitewing radiographs

We propose a new family of cost functions for signal and image recovery: they are composed of $\ell_1$ data fitting terms combined with concave regularization. We exhibit when and how to employ such cost functions. Our theoretical results show that the minimizers of these cost functions are such that each one of their entries is involved either in an exact data fitting component or in a null component of the regularization part. This is a strong and particular property that can be useful for various image recovery problems. The minimization of such cost functions presents a computational challenge. We propose a fast minimization algorithm to solve this numerical problem. The experimental results show the effectiveness of the proposed algorithm. All illustrations and numerical experiments give a flavor of the possibilities offered by the minimizers of this new family of cost functions in solving specialized image processing tasks.

On $\ell_1$ Data Fitting and Concave Regularization for Image Recovery

Dental biometrics is used in forensic dentistry to identify or verify persons based on their dental radiographs. This paper presents a method for human identification based on dental work information. The proposed method works with three main processing steps: segmentation (feature extraction), creation of a dental code, and matching. In the segmentation step, seed points of the dental works are detected by thresholding. The final segmentation is obtained with a snake (active contour) algorithm. The dental code is defined from the position (upper or lower), the size of the dental works, and distance between neighboring dental works. The matching stage is performed with the Edit distance (levenshtein distance). The costs for the insertion, deletion and substitution operations were adapted to make the matching algorithm more sensitive. The method was tested on a database including 68 dental radiographs and the results are encouraging.

Dental Biometrics: Human Identification Based On Dental Work Information

Laryngeal Electromyography: Electrode Guidance Based on 3-Dimensional Magnetic Resonance Tomography Images of the Larynx

A fully automated trabecular bone structural analysis tool based on T2* -weighted magnetic resonance imaging.

In the history of civilization, the human identification based on dental information was first reported in the Roman Empire, when Nero’s mother, Agripina, ordered the killing of Loilla Paulina, who was later identified by her dental caries and bad dental occlusion (Couto, 2009) The first treatise on human identification using dental records was conducted, in 1897, by Dr Oscar Amoedo Valdes (1863-1945), a Cuban doctor, president of the French Dental Society and professor of the Paris Dental School, who applied a dental-based identification technique in order to reveal the identity of victims of a disaster which occurred in Paris (Amoedo, 1897) Since Dr Amoedo’s work, the Forensic Dentistry has attracted much attention, and the importance of using dental records for human identification is nowadays accepted worldwide (Chen & Jain, 2005) During the last decade, dental records have been extensively used in order to identify the victims of massive disasters, such as the 9/11 terrorist attack in New York (O’Shaughnessy, 2002) and the tsunami in Asia (Thepgumpanat, 2005) In Forensic Dentistry, the human experts perform manual comparisons of ante-mortem (AM) and post-mortem (PM) dental records, looking for similarities (Jain & Chen, 2004) During this manual approach, the main characteristics used to compare dental records are: the presence or absence of a specific tooth, the morphology and dental restoration of the teeth, periodontal tissue characteristics, pathologies and other anatomical features Figure 1 shows panoramic radiographs of two distinct individuals One can easily observe several differences between these radiographs In contrast to other popular biometric characteristics, dental features do change over time, causing great difficulties during the identification task The teeth can change in appearance as a result of dental restorations, or can be missing altogether due to an accident which occurred after the AM records were taken For this reason, although accepted in courts of law, dental based identification is considered less reliable than other biometric methods (Jain et al, 2003) Figure 2 shows panoramic radiographs of the same individual taken at two separate occasions during a period of three years The dental patterns are almost the same, but changes due to dental restorations can be observed Despite known drawbacks of these identification methods, dental information may be the only available mean for identification in many disaster scenarios and mass accidents like fire and plane crashes The other popular methods of identification are impossible since physical traits like faces and fingerprints are, in general, completely destroyed in such events 3

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Dental Biometrics for Human Identification

Introduction: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a very promising method for noninvasive assessment of renal function such as renal perfusion or glomular filtration rate. The acquisition of DCE-MRI for that purpose is usually performed during free breathing because the scan duration, necessary for data analysis, is typically in the order of several minutes. The physiological motion is therefore clearly visible in the time series data, measured with a snapshot technique. For a pixel-by-pixel analysis (e.g. perfusion map) or small ROI’s (cortex), the data suffer from severe noise like artifacts (see Fig. 1a). Furthermore, the motion leads to a blurring and a bias of derived parameters of the individual compartments. Image registration is therefore a very important preprocessing step for the analysis of DCE-MRI data from moving organs. However, image registration is a challenging task due to the signal enhancement induced by contrast media [1, 2]. To overcome that problem, an image registration procedure was implemented which derives a template image series with the underlying signal time course. The original dynamic time series (source images) is registered by elastic registration to this virtual template. It is demonstrated that the algorithm is able to reduce motion artifacts to a high extend and allows a more differentiated analysis of several kidney tissue types such as renal cortex and renal medulla.

Michael Hofer

Papers

Dental Biometrics: Human Identification Based On Dental Work Information

Laryngeal Electromyography: Electrode Guidance Based on 3-Dimensional Magnetic Resonance Tomography Images of the Larynx

A fully automated trabecular bone structural analysis tool based on T2* -weighted magnetic resonance imaging.

Dental Biometrics for Human Identification

DCE-MRI Non-Rigid Kidney Registration