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Tratamiento de los tumores malignos del oído

EMC - Otorrinolaringología 2025年第1期54卷 1-12页

作者： G. Creff F. Jegoux Service d’oto-rhino-laryngologie – chirurgie cervicofaciale CHU de Rennes 2 rue Henri-Le-Guilloux 35000 Rennes France MediCIS LTSI (Image and Signal Processing Laboratory) Inserm U1099 2 avenue du Professeur-Léon-Bernard 35043 Rennes France

Los tumores malignos del oído engloban lesiones desarrolladas a partir de entidades anatómicas compuestas por estructuras tisulares diferentes, lo que explica su gran disparidad de forma clínica y, por tanto, de tratamiento. En primer lugar, la mayoría de los tumores del pabellón son tumores cutáneos (carcinoma basocelular, epidermoide, melanoma) y su estrategia diagnóstica y terapéutica es idéntica a la de otras localizaciones de tumores dermatológicos. En el conducto auditivo externo (CAE), las lesiones tumorales simulan la sintomatología de las otitis externas. Se debe realizar una biopsia sistemáticamente en caso de otitis externa refractaria al tratamiento médico bien realizado. En esta localización, además de los tumores cutáneos habituales, se observan los adenocarcinomas y los carcinomas adenoides quísticos, desarrollados a partir de las células ceruminosas y glandulares del CAE. Los tumores del oído medio son menos frecuentes y pueden ser difíciles de diferenciar de los tumores del CAE que invaden el oído medio. Por último, los tumores malignos del conducto auditivo interno son principalmente schwannomas malignos, bien primarios, bien secundarios a la irradiación de un schwannoma benigno. Los tumores del saco endolinfático suelen diagnosticarse de forma tardía, debido a su evolución lenta, y obligan a buscar un síndrome de Von Hippel-Lindau. Los tumores óseos del peñasco suelen ser primarios (sarcomas) o secundarios (metástasis óseas de cánceres de pulmón, gastrointestinales, renales o de mama). Por último, en los niños, el diagnóstico mayoritario es el de histiocitosis de células de Langerhans. Por tanto, la presentación clínica y el tratamiento dependen de la localización tumoral, pero también de la accesibilidad a la biopsia diagnóstica.

关键词： Carcinoma basocelular Carcinoma epidermoide Melanoma Pabellón auricular Conducto auditivo externo Oído medio Conducto auditivo interno Schwannoma Saco endolinfático Histiocitosis de células de Langerhans

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P-177 FDG-PET/CT-based prognostic survival model after surgery for head and neck cancer

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Oral Oncology 2021年 118卷 23-23页

作者： Creff, Gwenaelle Jegoux, Franck Palard, Xavier Depeursinge, Adrien Abgral, Ronan Marianowski, Remi Leclere, Jean-Christophe Eugene, Thomas Malard, Olivier de Crevoisier, Renaud Devillers, Anne Castelli, Joel Department of Head and Neck Surgery Rennes France LTSI (Image and Signal Processing Laboratory) INSERM U1099 Rennes France Department of Nuclear Medicine Cancer Institute Eugène Marquis Rennes France Institute of Information Systems University of Applied Sciences Switzerland Department of Nuclear Medicine University Hospital Brest France Department of Head and Neck Surgery University Hospital Brest France Department of Nuclear Medicine University Hospital Nantes France Department of Otolaryngology–Head and Neck Surgery Nantes France Department of Radiation Oncology Cancer Institute Eugène Marquis Rennes France

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Pseudo-CT generation by conditional inference random forest for MRI-based radiotherapy treatment planning

Pseudo-CT generation by conditional inference random forest ...

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European signal processing Conference (EUSIPCO)

作者： Axel Largent Jean-Claude Nunes Hervé Saint-Jalmes Antoine Simon Nicolas Perichon Anais Barateau Chloé Hervé Caroline Lafond Peter B. Greer Jason A. Dowling Renaud de Crevoisier Oscar Acosta INSERM UMR 1099 Rennes France Laboratory of Signal and Image Processing (LTSI) Rennes France Radiotherapy department Centre Eugéne Marquis Rennes France School of Mathematical and Physical Sciences University of Newcastle Newcastle Australia CSIRO Australian e-Health Research Centre Herston Queensland Australia

Dose calculation from MRI is a topical issue. New treatment systems combining a linear accelerator with a MRI have been recently being developed. MRI has good soft tissue contrast without ionizing radiation exposure. However, unlike CT, MRI does not provide electron density information necessary for dose calculation. We propose in this paper a machine learning method to simulate a CT from a target MRI and co-registered CT-MRI training set. Ten prostate MR and CT images have been considered. Firstly, a reference image was randomly selected in the training set. A common space has been built thanks to affine registrations between the training set and the reference image. Multiscale image descriptors such as spatial information, gradients and texture features were extracted from MRI patches at dilïerent levels of a Gaussian pyramid and used as voxel-wise characteristics in the learning scheme. A Conditional Inference Random Forest (CIRF) modelled the relation between MRI descriptors and CT patches. For validation, test images were spatially normalized and the same descriptors were computed to generate a new pCT. Leave-one out experiments were performed. We obtained a MAE = 45.79 (pCT vs CT). Dose volume histograms inside PTV and organs at risk are in close agreement. The D98% was 0.45 % (inside PTV) and the 3D gamma pass rate (1mm, 1%) was 99,2%. Our method has better results than direct bulk assignment. And the results suggest that the method may be used for dose calculations in an MR based planning system.

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New clustering of the spikes morphology based on dynamic clouds in partial epilepsy

New clustering of the spikes morphology based on dynamic clo...

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Science and Information Conference (SAI)

作者： Ousmane Khouma Mamadou Lamine Ndiaye Idy Diop Abdou Khadre Diop Sidi Mohamed Farsi Birahime Diouf Jean-jacques Montois Polytechnic School Cheikh Anta Diop University Dakar Senegal Signal and Image Processing Laboratory (LTSI U642 INSERMRENNES 1) Rennes France

ISBN: (纸本)9781467384612

The acquisition of EEG signals can be done during days. In this paper, the signals of depth Stereo-Electroencephalography (SEEG) are used. In SEEG signal, several inter-ictal paroxystic events (IPE) are found, they appear between the crises. To analyze their distribution, they should initially be detected by separating them from the basic activity. After the detection step, we implement a clustering process to distinguish IPE or spike according to their morphology. Results of detection and clustering would characterize a link between space-time distribution of IPE and the arrival of the crises. It would be thus a contribution on the diagnosis of the partial epilepsies.

关键词： Morphology Electroencephalography Clustering algorithms Brain models Epilepsy Euclidean distance

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GinFlow: A Decentralised Adaptive Workflow Execution Manager

GinFlow: A Decentralised Adaptive Workflow Execution Manager

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International Symposium on Parallel and Distributed processing (IPDPS)

作者： Javier Rojas Balderrama Matthieu Simonin Cédric Tedeschi Signal and Image Processing Laboratory (LTSI) Inserm — Université de Rennes 1 France Inria Institute for Research in IT and Random Systems (IRISA) Université de Rennes 1 France

ISBN: (纸本)9781509021413

Workflow-based computing has become a dominant paradigm to design and execute scientific applications. After the initial breakthrough of now standard workflow management systems, several approaches have recently proposed to decentralise the coordination of the execution. In particular, shared space-based coordination has been shown to provide appropriate building blocks for such a decentralised execution. Uncertainty is also still a major concern in scientific workflows. The ability to adapt the workflow, change its shape and switch for alternate scenarios on-the-fly is still missing in workflow management systems. In this paper, based on a shared space approach, we firstly devise a programmatic way to specify such adaptive workflows. We use a reactive, rule-based programming model to modify the workflow description by changing its associated direct acyclic graph on-the-fly without needing to stop and restart the execution from the beginning. Secondly, we present the GinFlow middleware, a resilient decentralised workflow execution manager implementing these concepts. Through a set of deployments of adaptive workflows of different characteristics, we discuss the GinFlow performance and resilience and show the limited overhead of the adaptiveness mechanism, making it a promising decentralised adaptive workflow execution manager.

关键词： Programming Engines Adaptation models Chemicals Middleware Resilience Computer architecture

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Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care

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Nature communications 2019年第1期10卷 588页

作者： Lena Maier-Hein Matthias Eisenmann Annika Reinke Sinan Onogur Marko Stankovic Patrick Scholz Tal Arbel Hrvoje Bogunovic Andrew P Bradley Aaron Carass Carolin Feldmann Alejandro F Frangi Peter M Full Bram van Ginneken Allan Hanbury Katrin Honauer Michal Kozubek Bennett A Landman Keno März Oskar Maier Klaus Maier-Hein Bjoern H Menze Henning Müller Peter F Neher Wiro Niessen Nasir Rajpoot Gregory C Sharp Korsuk Sirinukunwattana Stefanie Speidel Christian Stock Danail Stoyanov Abdel Aziz Taha Fons van der Sommen Ching-Wei Wang Marc-André Weber Guoyan Zheng Pierre Jannin Annette Kopp-Schneider Division of Computer Assisted Medical Interventions (CAMI) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. l.maier-hein@dkfz.de. Division of Computer Assisted Medical Interventions (CAMI) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. Centre for Intelligent Machines McGill University Montreal QC H3A0G4 Canada. Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna 1090 Vienna Austria. Science and Engineering Faculty Queensland University of Technology Brisbane QLD 4001 Australia. Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore MD 21218 USA. CISTIB - Center for Computational Imaging & Simulation Technologies in Biomedicine The University of Leeds Leeds Yorkshire LS2 9JT UK. Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center 6525 GA Nijmegen The Netherlands. Institute of Information Systems Engineering TU Wien 1040 Vienna Austria. Complexity Science Hub Vienna 1080 Vienna Austria. Heidelberg Collaboratory for Image Processing (HCI Heidelberg University 69120 Heidelberg Germany. Centre for Biomedical Image Analysis Masaryk University 60200 Brno Czech Republic. Electrical Engineering Vanderbilt University Nashville TN 37235-1679 USA. Institute of Medical Informatics Universität zu Lübeck 23562 Lübeck Germany. Division of Medical Image Computing (MIC) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. Institute for Advanced Studies Department of Informatics Technical University of Munich 80333 Munich Germany. Information System Institute HES-SO Sierre 3960 Switzerland. Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC 3015 GD Rotterdam The Netherlands. Department of Computer Science University of Warwick Coventry CV4 7AL UK. Department of Radiation Oncology Massachusetts General Hospital Boston MA

In the original version of this Article the values in the rightmost column of Table 1 were inadvertently shifted relative to the other columns. This has now been corrected in the PDF and HTML versions of the Article.

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Ambulatory physical activity representation and classification using spectral distances approach

Ambulatory physical activity representation and classificati...

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International Conference on Advances in Biomedical Engineering (ICABME)

作者： Hala Abdul Rahman Guy Carrault Di Ge Hassan Amoud Jacques Prioux Alexis Le Faucheur Remy Dumond Laboratory of Signal and Image Processing (LTSI) University of Rennes1 Rennes France Sport and Health Sciences(M2S) ENS -Ker Lann Campus Bruz Laboratory of Movement France

Methods for monitoring the human physical activity are recently investigated in order to assess the health status of the individuals and thus promote a healthier lifestyle. This paper proposes `dist-colorimetrics', a methodology that aims to represent and classify ambulatory activities based on the spectral distances measures. A data collection platform including four accelerometer sensors mounted on the chest, ankle, wrist and hip, is used to record five activities: running, walking, cycling, resting and car riding. The proposed approach converts raw acceleration data into relevant spectral distances parameters. A 2D colored illustration of these parameters provides efficient visual representation as to the similarity and the variation among activities. For a further validation in terms of recognition performance, the `dist-colorimetrics' model was trained and tested by implementing three classification techniques, namely the Naïve Bayes, the K-nearest neighbors and the decision tree. The results showed that the system reached up to 98.12% of overall recognition accuracy. With further improvement in the modeling of each activity, we have reason to believe that the spectral distances are a promising approach to distinguish between different physical activities.

关键词： Sensors Biomedical measurement Accelerometers Legged locomotion Accuracy Brain modeling Monitoring

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ECG Denoising Using Mutual Information Based Classification of IMFs and Interval Thresholding

ECG Denoising Using Mutual Information Based Classification ...

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International Conference on Telecommunications and signal processing

作者： Marjaneh Taghavi Mohammad B. Shamsollahi Lotfi Senhadji School of Engineering and Science Sharif University of Technology International Campus Kish Island Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology Laboratoire Traitement du Signal et de l'Image (LTSI) Universitede Rennes 1

ISBN: (纸本)9781479984992

The Electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Therefore, the quality of information extracted from the ECG has a vital role. In real recordings, ECG is corrupted by artifacts such as prolonged repolarization, respiration, changes of electrode position, muscle contraction, and power line interface. In this paper, a denoising technique for ECG signals based on Empirical Mode Decomposition (EMD) is proposed. We use Ensemble Empirical Mode Decomposition (EEMD) to overcome the limitations of EMD. Moreover, to overcome the limitations of thresholding methods we use the combination of mutual information and two EMD based interval thresholding approaches. Our new method is evaluated on ECG signals available in MIT-BIH database. This method is compared with two EEMD based interval thresholding methods. The results show that our proposed method has a better signal to Noise Ratio improvement (SNRimp) and a lower Mean Square Error (MSE) than the other two methods.

关键词： Ensemble Empirical Mode Decomposition Denoising Mutual Information Instantaneous Half Period Interval Thresholding ECG

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Composite annotation for heart development

Composite annotation for heart development

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2nd International Conference on Biomedical Ontology, ICBO 2011

作者： Abdulla, Tariq Imms, Ryan Schleich, Jean-Marc Summers, Ron Research School of Systems Engineering Loughborough University Loughborough United Kingdom LTSI Signal and Image Processing Laboratory Universite de Rennes 1 Rennes France

This paper describes progress made in combining multiple ontologies in a post- coordinated approach. This is applied to the annotation of phenotvpes relevant to heart development and congenital heart diseases. The aim is to provide coordination for multiscale modeling and simulation that is presently being conducting in this field. Cardiac development is well understood within discrete levels of analysis. The application of the multiscale framework gives added value by unlocking relationships between genetic-based information at one level of analysis and the emergent phenotype at the cell and organ levels of abstraction. The challenge for a semantic representation is that this field encompasses multiple spatial and temporal scales. As a consequence, relevant terms come from a wide range of biomedical domains, and are therefore contained in several reference ontologies. The strategy for composite annotation provides a method for linking between multiscale measurement and modeling.

关键词： Ontology

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A Dynamical Model for Generating Synthetic Phonocardiogram signals

A Dynamical Model for Generating Synthetic Phonocardiogram S...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Ali Almasi Mohammad B. Shamsollahi Lotfi Senhadji Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology LTSI Rennes 1 University

ISBN: (纸本)9781424441211

In this paper we introduce a dynamical model for Phonocardiogram (PCG) signal which is capable of generating realistic synthetic PCG signals. This model is based on PCG morphology and consists of three ordinary differential equations and can represent various morphologies of normal PCG signals. Beat-to-beat variation in PCG morphology is significant so model parameters vary from beat to beat. This model is inspired of Electrocardiogram (ECG) dynamical model proposed by McSharry et al. and can be employed to assess biomedical signal processing techniques.

关键词： kinetic model phonocardiography Ordinary differential equation Beat Electrocardiography model parameters medical signal processing

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