0000000000235302

AUTHOR

Guillaume Lemaitre

showing 22 related works from this author

Wood fiber orientation assessment based on punctual laser beam excitation: A preliminary study

2016

International audience; The EU imposes standards for the use of wood in structural applications. Local singularities such as knots affect the wood mechanical properties. They can be revealed by looking at the wood fiber orientation. For this reason, many methods were proposed to estimate the orientation of wood fiber using optical means, X-rays, or scattering measurement techniques. In this paper, an approach to assess the wood fiber orientation based on thermal ellipsometry is developed. The wood part is punctually heated with a Nd-YAG Laser and the thermal response is acquired by an infrared camera. The thermal response is elliptical due to the propagation of the heat through and along th…

Materials scienceInfraredOrientation (computer vision)Scatteringbusiness.industry[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyLaserEllipse01 natural scienceslaw.invention010309 opticsOpticslawEllipsometry0103 physical sciencesThermal0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingFiberbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingProceedings of the 2016 International Conference on Quantitative InfraRed Thermography
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Innovative Tools for Sound Sketching Combining Vocalizations and Gestures

2016

International audience; Designers are used to produce a variety of physical and digital representations at different stages of the design process. These intermediary objects (IOs) do support the externalization of ideas and the mediation with the different stakeholders. In the same manner, sound designers deliver several intermediate sounds to their clients, through iteration and refinement. In fact, these preliminary sounds are sound sketches representing the intermediate steps of an evolving creation. In this paper we reflect on the method of sketching sounds through vocalizations and gestures, and how a technological support, grounded in the understanding of the design practice, can fost…

Sound Designgeographygeography.geographical_feature_categoryInteractionSettore INF/01 - InformaticaScope (project management)Computer scienceSound design05 social sciences01 natural sciencesTransparency (behavior)Variety (cybernetics)VocalizationGesture[SPI]Engineering Sciences [physics]Human–computer interaction0103 physical sciencesMediation0501 psychology and cognitive sciencesEngineering design process010301 acoustics050107 human factorsSound (geography)GestureProceedings of the Audio Mostly 2016
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Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review

2015

Prostate cancer is the second most diagnosed cancer of men all over the world. In the last few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed to improve diagnosis. In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systems have been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field of research for the last 10years. This survey aims to provide a comprehen…

Malemedicine.medical_specialtyTime FactorsHealth InformaticsCAD[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingProstate cancerImage Processing Computer-AssistedMedicineHumansMass ScreeningMedical physicsDiagnosis Computer-AssistedObserver VariationMulti parametricmedicine.diagnostic_testbusiness.industryCarcinomaProstatic NeoplasmsReproducibility of ResultsMagnetic resonance imagingmedicine.diseaseMagnetic Resonance ImagingComputer aided detection3. Good healthComputer Science ApplicationsClinical PracticeMultiple factorsComputer-aided diagnosisResearch DesignNeural Networks ComputerNeoplasm Gradingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMedical InformaticsSoftware
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Video-Based Depression Detection Using Local Curvelet Binary Patterns in Pairwise Orthogonal Planes

2016

International audience; Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage of these methods is that they have significantly lower computational requirements, as the extracted features are of very low dimensionality. This is achieved by modifying the previously proposed algorithm which considers Three-Orthogonal-Planes, to only Pairwise-Ort…

Local binary patternsFeature extractionVideo Recording02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMachine learningcomputer.software_genreField (computer science)0502 economics and business0202 electrical engineering electronic engineering information engineeringCurveletHumansDiagnosis Computer-Assisted[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryDepression05 social sciencesReproducibility of ResultsPattern recognitionActive appearance modelFaceBenchmark (computing)020201 artificial intelligence & image processingPairwise comparisonArtificial intelligencebusinessPsychologycomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing050203 business & managementAlgorithmsCurse of dimensionality
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On the effectiveness of vocal imitations and verbal descriptions of sounds

2014

cote interne IRCAM: Lemaitre14b; None / None; International audience; Describing unidentified sounds with words is a frustrating task and vocally imitating them is often a convenient way to address the issue. This article reports on a study that compared the effectiveness of vocal imitations and verbalizations to communicate different referent sounds. The stimuli included mechanical and synthesized sounds and were selected on the basis of participants' confidence in identifying the cause of the sounds, ranging from easy-to-identify to unidentifiable sounds. The study used a selection of vocal imitations and verbalizations deemed adequate descriptions of the referent sounds. These descriptio…

Sound (medical instrument)Settore INF/01 - InformaticaAcoustics and UltrasonicsSpeech recognitionAcoustics[SCCO.NEUR]Cognitive science/Neuroscience05 social sciencesReferent050105 experimental psychologyTask (project management)03 medical and health sciences[SPI]Engineering Sciences [physics]vocal imitations0302 clinical medicineArts and Humanities (miscellaneous)Selection (linguistics)Identifiability0501 psychology and cognitive sciencesNA[INFO]Computer Science [cs]Psychology030217 neurology & neurosurgery
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Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection

2016

International audience; This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with Diabetic Macular Edema (DME) versus normal subjects. Optical Coherence Tomography (OCT) has been a valuable diagnostic tool for DME, which is among the most common causes of irreversible vision loss in individuals with diabetes. Here, a classification framework with five distinctive steps is proposed and we present an extensive study of each step. Our method considers combination of various pre-processings in conjunction with Local Binary Patterns (LBP) features and different mapping strategies. Using linear and non-linear cl…

genetic structures[INFO.INFO-IM] Computer Science [cs]/Medical Imaging[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Segmentationlcsh:OphthalmologySpeckleLBPDiagnosisPrevalencePreprocessorComputer visionSegmentationmedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingExperimental validationDiabetic Macular Edema[ SDV.MHEP.OS ] Life Sciences [q-bio]/Human health and pathology/Sensory OrgansOptical Coherence Tomography[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingResearch ArticleArticle SubjectLocal binary patterns03 medical and health sciencesSpeckle patternOptical coherence tomography[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathologyMedical imagingmedicineDME[INFO.INFO-IM]Computer Science [cs]/Medical ImagingCoherence (signal processing)Texture[SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory OrgansRetinopathy[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitioneye diseasesOphthalmologyOCTlcsh:RE1-994030221 ophthalmology & optometryImagesArtificial intelligencebusiness030217 neurology & neurosurgery[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Combining gestures and vocalizations to imitate sounds

2015

International audience; Communicating about sounds is a difficult task without a technical language, and naïve speakers often rely on different kinds of non-linguistic vocalizations and body gestures (Lemaitre et al. 2014). Previous work has independently studied how effectively people describe sounds with gestures or vocalizations (Caramiaux, 2014, Lemaitre and Rocchesso, 2014). However, speech communication studies suggest a more intimate link between the two processes (Kendon, 2004). Our study thus focused on the combination of manual gestures and non-speech vocalizations in the communication of sounds. We first collected a large database of vocal and gestural imitations of a variety of …

Acoustics and UltrasonicsComputer scienceInformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)Speech recognition02 engineering and technologyRepresentation (arts)[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]Loudness[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SCCO]Cognitive science0202 electrical engineering electronic engineering information engineering[ INFO.INFO-NE ] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]050107 human factorsComputingMilieux_MISCELLANEOUSSound (medical instrument)05 social sciences[ SHS.ANTHRO-SE ] Humanities and Social Sciences/Social Anthropology and ethnology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ SCCO.COMP ] Cognitive science/Computer science[SCCO.PSYC] Cognitive science/Psychology[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD][ SCCO.NEUR ] Cognitive science/Neuroscience[SCCO.PSYC]Cognitive science/Psychology[ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.EIAH]Computer Science [cs]/Technology for Human Learning[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGesture[ SHS.MUSIQ ] Humanities and Social Sciences/Musicology and performing artsAcoustics[SCCO.COMP]Cognitive science/Computer scienceArts and Humanities (miscellaneous)[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC]0501 psychology and cognitive sciences[ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]Set (psychology)[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph][SPI.ACOU] Engineering Sciences [physics]/Acoustics [physics.class-ph][SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts[ INFO.INFO-ET ] Computer Science [cs]/Emerging Technologies [cs.ET][SCCO.NEUR]Cognitive science/Neuroscience020207 software engineering[SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnologyVariety (linguistics)loudness[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Noise (video)[ INFO.INFO-SD ] Computer Science [cs]/Sound [cs.SD]
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Tackling the Problem of Data Imbalancing for Melanoma Classification

2016

Comunicació de congrés presentada a: 3rd International Conference on Bioimaging, BIOIMAGING 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016, Roma, Italy Malignant melanoma is the most dangerous type of skin cancer, yet melanoma is the most treatable kind of cancer when diagnosed at an early stage. In this regard, Computer-Aided Diagnosis systems based on machine learning have been developed to discern melanoma lesions from benign and dysplastic nevi in dermoscopic images. Similar to a large range of real world applications encountered in machine learning, melanoma classification faces the challenge of imbalanced data, where …

medicine.medical_specialtyFeature vectorMELANOMA02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingImbalanced dataCLASSIFICATION030218 nuclear medicine & medical imaging03 medical and health sciencesDERMOSCOPY0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineIMBALANCEDStage (cooking)Melanoma[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryMelanomaCancermedicine.diseaseDermatologyData balancingFeature (computer vision)020201 artificial intelligence & image processingEnginyeria biomèdicaSkin cancerbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingBiomedical engineering
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Outils innovants pour la création d’esquisses sonores combinant vocalisations et gestes

Les designers produisent différents types de représentations physiques et/ou digitales lors des différentes phases d'un processus de design. Ces objets intermédiaires de représentation permettent et supportent l'incarnation des idées du designer, de les externaliser, mais aussi la médiation entre les personnes qui sont impliquées dans les différentes phases du design (designers produits, ingénieurs, marketing, ...). Les designers sonores, eux aussi, produisent des sons intermédiaires pour les présenter aux commanditaires par un processus itératif de raffinement de ces propositions. Ainsi ces différents sons intermédiaires sont des esquisses sonores qui représentent les différentes étapes in…

sound designSettore INF/01 - InformaticaSettore ICAR/13 - Disegno Industriale
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A boosting approach for prostate cancer detection using multi-parametric MRI

2015

International audience; Prostate cancer has been reported as the second most frequently diagnosed men cancers in the world. In the last decades, new imaging techniques based on MRI have been developed in order to improve the diagnosis task of radiologists. In practise, diagnosis can be affected by multiple factors reducing the chance to detect potential lesions. Computer-aided detection and computer-aided diagnosis have been designed to answer to these needs and provide help to radiologists in their daily duties. In this study, we proposed an automatic method to detect prostate cancer from a per voxel manner using 3T multi-parametric Magnetic Resonance Imaging (MRI) and a gradient boosting …

medicine.medical_specialty02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcomputer.software_genremulti-parametric MRI03 medical and health sciencesProstate cancer0302 clinical medicineVoxelArea under curve0202 electrical engineering electronic engineering information engineeringmedicine[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMulti parametricmedicine.diagnostic_testbusiness.industry020207 software engineeringMagnetic resonance imagingmedicine.diseaseprostate cancer3. Good healthMultiple factorsComputer-aided diagnosis030220 oncology & carcinogenesisGradient boostingcomputer-aided diagnosisGradient boostingRadiologybusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests

2016

International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…

Computer scienceSparse codingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformImage processingDermoscopy02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHistogram0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationMelanoma[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryMelanomaCancerPattern recognitionImage segmentationSparse approximationRandom forestsmedicine.diseaseClassificationRandom forest020201 artificial intelligence & image processingArtificial intelligenceSkin cancerNeural codingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Embodied sound design

2018

Abstract Embodied sound design is a process of sound creation that involves the designer’s vocal apparatus and gestures. The possibilities of vocal sketching were investigated by means of an art installation. An artist–designer interpreted several vocal self-portraits and rendered the corresponding synthetic sketches by using physics-based and concatenative sound synthesis. Both synthesis techniques afforded a broad range of artificial sound objects, from concrete to abstract, all derived from natural vocalisations. The vocal-to-synthetic transformation process was then automated in SEeD, a tool allowing to set and play interactively with physics- or corpus-based sound models. The voice-dri…

Range (music)sound synthesisProcess (engineering)Sound designHuman Factors and Ergonomicsvocal sketchingsonic interaction design01 natural sciences050105 experimental psychologyEducationHuman–computer interaction0103 physical sciencesSettore ICAR/13 - Disegno IndustrialeNatural (music)0501 psychology and cognitive sciencesSet (psychology)010301 acousticsSound (geography)embodimentSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionigeographygeography.geographical_feature_categorySettore INF/01 - Informatica05 social sciencesGeneral EngineeringSound designHuman-Computer InteractionHardware and ArchitectureEmbodied cognitionSound design; embodiment; vocal sketching; sound synthesisSoftwareGesture
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Evidence for a spatial bias in the perception of sequences of brief tones

2013

Listeners are unable to report the physical order of particular sequences of brief tones. This phenomenon of temporal dislocation depends on tone durations and frequencies. The current study empirically shows that it also depends on the spatial location of the tones. Dichotically testing a three-tone sequence showed that the central tone tends to be reported as the first or the last element when it is perceived as part of a left-to-right motion. Since the central-tone dislocation does not occur for right-to-left sequences of the same tones, this indicates that there is a spatial bias in the perception of sequences. © 2013 Acoustical Society of America.

AdultMaleAcoustic Stimulation; Adult; Audiometry Pure-Tone; Dichotic Listening Tests; Female; Humans; Male; Pattern Recognition Physiological; Psychoacoustics; Time Factors; Young Adult; Pitch Perception; Time Perception; Acoustics and Ultrasonics; Arts and Humanities (miscellaneous); Medicine (all)Time FactorsAcoustics and UltrasonicsTime FactorSpeech recognitionAcousticsmedia_common.quotation_subjectspatial biasAcoustics and UltrasonicMotion (physics)Dichotic Listening TestsDichotic Listening TestTone (musical instrument)Young AdultPsychoacousticArts and Humanities (miscellaneous)Dislocation (syntax)PerceptionHumansspatial bias; temporal dislocationPsychoacousticstemporal dislocationPitch PerceptionMathematicsmedia_commonSequenceSettore INF/01 - InformaticaDichotic listeningMedicine (all)Time perceptionAcoustic StimulationPattern Recognition PhysiologicalTime PerceptionAudiometry Pure-ToneFemalePsychoacousticsHuman
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Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections.

2016

This paper deals with the automated detection of Diabetic Macular Edema (DME) on Optical Coherence Tomography (OCT) volumes. Our method considers a generic classification pipeline with preprocessing for noise removal and flattening of each B-Scan. Features such as Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are extracted and combined to create a set of different feature vectors which are fed to a linear-Support Vector Machines (SVM) Classifier. Experimental results show a promising sensitivity/specificity of 0.75/0.87 on a challenging dataset.

Support Vector Machinegenetic structuresDatabases FactualComputer science[INFO.INFO-IM] Computer Science [cs]/Medical Imaging02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciences[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringImage Processing Computer-AssistedSegmentationComputer visionmedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingDiabetic retinopathyHistogram of oriented gradientsmedicine.anatomical_structure020201 artificial intelligence & image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingTomography Optical CoherenceLocal binary patternsFeature vectorDiabetic macular edemaFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingSensitivity and SpecificityMacular Edema010309 opticsOptical coherence tomographyHistogram0103 physical sciencesmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumansMacular edema[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingRetinaDiabetic Retinopathybusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionImage segmentationmedicine.diseaseeye diseasesSupport vector machineComputingMethodologies_PATTERNRECOGNITIONsense organsArtificial intelligencebusinessAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors

2015

International audience; Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the b…

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCAD02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingBI-RADS lexiconOptimization based Segmentation030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineBreast cancerCut0202 electrical engineering electronic engineering information engineeringMedical imagingMedicineComputer visionBreast ultrasound[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelmedicine.diagnostic_testbusiness.industryBreast Ultra-SoundGraph-CutsImage segmentationmedicine.disease3. Good healthComputingMethodologies_PATTERNRECOGNITIONComputer-aided diagnosis020201 artificial intelligence & image processingMachine-Learning based SegmentationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Normalization of T2W-MRI Prostate Images using Rician a priori

2016

International audience; Prostate cancer is reported to be the second most frequently diagnosed cancer of men in the world. In practise, diagnosis can be affected by multiple factors which reduces the chance to detect the potential lesions. In the last decades, new imaging techniques mainly based on MRI are developed in conjunction with Computer-Aided Diagnosis (CAD) systems to help radiologists for such diagnosis. CAD systems are usually designed as a sequential process consisting of four stages: pre-processing, segmentation, registration and classification. As a pre-processing, image normalization is a critical and important step of the chain in order to design a robust classifier and over…

Normalization (statistics)Computer scienceNormalization (image processing)T2W-MRI02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicineProstateRician fading0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentation[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingpre-processingProstate cancermedicine.diagnostic_testbusiness.industryCancerMagnetic resonance imagingImage segmentationmedicine.diseasemedicine.anatomical_structurenormalizationComputer-aided diagnosisA priori and a posteriori020201 artificial intelligence & image processingcomputer-aided diagnosisArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Computer-Aided Detection for Prostate Cancer Detection based on Multi-Parametric Magnetic Resonance Imaging

2017

International audience; Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. In the last decades, new imaging techniques based on magnetic resonance imaging (MRI) have been developed improving diagnosis. In practice, diagnosis is affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and diagnosis (CAD) systems are being designed to help radiologists in their clinical practice. We propose a CAD system taking advantage of all MRI modalities (i.e., T2-W-MRI, DCE-MRI, diffusion weighted (DW)-MRI, MRSI). The aim of this CAD system was to provide a probabilistic map of cancer…

Malemedicine.medical_specialtySource codemedia_common.quotation_subject[INFO.INFO-IM] Computer Science [cs]/Medical ImagingContrast MediaCAD[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Prostatemedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML][SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingmedia_commonMulti parametricModality (human–computer interaction)[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingmedicine.diagnostic_testbusiness.industryProstatic NeoplasmsCancerMagnetic resonance imagingmedicine.diseaseMagnetic Resonance Imaging[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]3. Good healthmedicine.anatomical_structureRadiologybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgery
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A combined three-dimensional digitisation and subsurface defect detection data using active infrared thermography

2016

International audience; In recent years, NonDestructive Testing (NDT) systems have been upgraded with three-dimensional information. Indeed, combine the three-dimensional and thermal information allows a more meaningful analysis. In the literature, the data for NDT and three-dimensional (3D) reconstruction analysis are commonly acquired from independent systems. However, the use of two such systems leads to error analysis during the data registration. In an attempt to overcome such problems, we propose a single system based on active thermography approach using heat point-source stimulation to get the 3D digitization as well as subsurface defect detection. The experiments are conducted on s…

010302 applied physicsActive infraredbusiness.industryComputer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesError analysisNondestructive testing0103 physical sciencesThermographyData registrationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing010301 acousticsDigitization[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingRemote sensing
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Comparing identification of vocal imitations and computational sketches of everyday sounds

2016

International audience; Sounds are notably difficult to describe. It is thus not surprising that human speakers often use many imitative vocalizations to communicate about sounds. In practice,vocal imitations of non-speech everyday sounds (e.g. the sound of a car passing by) arevery effective: listeners identify sounds better with vocal imitations than with verbal descriptions, despite the fact that vocal imitations are often inaccurate, constrained by the human vocal apparatus. The present study investigated the semantic representations evoked by vocal imitations by experimentally quantifying how well listeners could match sounds to category labels. Itcompared two different types of sounds…

Acoustics and UltrasonicsComputer science[ SHS.MUSIQ ] Humanities and Social Sciences/Musicology and performing artsSpeech recognitionAcoustics[SCCO.COMP]Cognitive science/Computer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI]Engineering Sciences [physics][SCCO]Cognitive scienceArts and Humanities (miscellaneous)[ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC][ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC][ INFO.INFO-NE ] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSSound (medical instrument)[ INFO.INFO-ET ] Computer Science [cs]/Emerging Technologies [cs.ET][SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts[SCCO.NEUR]Cognitive science/Neuroscience[SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnologyIdentification (information)[ SHS.ANTHRO-SE ] Humanities and Social Sciences/Social Anthropology and ethnology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ SCCO.COMP ] Cognitive science/Computer science[ SCCO.NEUR ] Cognitive science/Neuroscience[INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD][ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.EIAH]Computer Science [cs]/Technology for Human Learning[ INFO.INFO-SD ] Computer Science [cs]/Sound [cs.SD][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Classifying DME vs Normal SD-OCT volumes: A review

2016

International audience; This article reviews the current state of automatic classification methodologies to identify Diabetic Macular Edema (DME) versus normal subjects based on Spectral Domain OCT (SD-OCT) data. Addressing this classification problem has valuable interest since early detection and treatment of DME play a major role to prevent eye adverse effects such as blindness. The main contribution of this article is to cover the lack of a public dataset and benchmark suited for classifying DME and normal SD-OCT volumes, providing our own implementation of the most relevant methodologies in the literature. Subsequently, 6 different methods were implemented and evaluated using this comm…

genetic structuresComputer scienceDiabetic macular edemaEarly detection[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMachine learningcomputer.software_genre01 natural sciences010309 optics03 medical and health sciences0302 clinical medicinebenchmark0103 physical sciencesmedicine[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingRetinaBlindnessbusiness.industryMachine Learning (ML)medicine.diseaseeye diseasesSpectral Domain OCT (SD-OCT)medicine.anatomical_structure030221 ophthalmology & optometryBenchmark (computing)Artificial intelligenceData miningsense organsDiabetic Macular Edema (DME)businesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Sketching Sound with Voice and Gesture

2015

Voice and gestures are natural sketching tools that can be exploited to communicate sonic interactions. In product and interaction design, sounds should be included in the early stages of the design process. Scientists of human motion have shown that auditory stimuli are important in the performance of difficult tasks and can elicit anticipatory postural adjustments in athletes. These findings justify the attention given to sound in interaction design for gaming, especially in action and sports games that afford the development of levels of virtuosity. The sonic manifestations of objects can be designed by acting on their mechanical qualities and by augmenting the objects with synthetic and…

geographygeography.geographical_feature_categorySettore INF/01 - InformaticaInformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)Computer scienceSpeech recognitionSound designInteraction designSound designsonic interaction design[PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph]Human-Computer InteractionimitationsProduct (mathematics)[SCCO.PSYC]Cognitive science/PsychologyNatural (music)Sound (geography)ComputingMilieux_MISCELLANEOUSGesture
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Classification of SD-OCT Volumes with LBP: Application to DME Detection

2015

International audience; This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with Diabetic Macular Edema (DME) versus normal subjects. Our method is based on Local Binary Patterns (LBP) features to describe the texture of Optical Coherence Tomography (OCT) images and we compare different LBP features extraction approaches to compute a single signature for the whole OCT volume. Experimental results with two datasets of respectively 32 and 30 OCT volumes show that regardless of using low or high level representations, features derived from LBP texture have highly discriminative power. Moreover, the experimen…

genetic structuresLocal binary patternsComputer scienceDiabetic macular edemaSpectral domain02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineOptical coherence tomographyDiscriminative modelLBP0202 electrical engineering electronic engineering information engineeringmedicineDMEComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingmedicine.diagnostic_testbusiness.industryeye diseasesDiabetic Macular EdemaOCT020201 artificial intelligence & image processingArtificial intelligencesense organsOptical Coherence Tomographybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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