Spatio-temporal resolution enhancement of vocal tract MRI sequences based on image registration

Martins, Ana L. D.; Mascarenhas, Nelson D. A.; Suazo, Cláudio Alberto Torres

doi:10.3233/ica-2011-0367

Cited by 16 publications

(5 citation statements)

References 26 publications

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“…The authors demonstrated that it is possible to acquire 3D imaging data of the vocal during a single sustained sound production stack (without sound repetitions). In line with this work, other studies have been performed, particularly for European Portuguese sounds [12,24].…”

Section: Measuring and Modelling Speech: A Reviewsupporting

confidence: 73%

3D Vocal Tract Reconstruction Using Magnetic Resonance Imaging Data to Study Fricative Consonant Production

Ventura

Freitas

Ramos

et al. 2015

Lecture Notes in Computational Vision and Biomechanics

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The development of Magnetic Resonance Imaging (MRI) has grown rapidly in clinical practice. Currently, the use of MRI in speech research provides useful and accurate qualitative and quantitative data of speech articulation. The aim of this work was to describe an effective method to extract vocal tract and compute their volumes during speech production from MRI images. Using a 3.0 Tesla MRI system, 2D and 3D images of the vocal tract were collected and used to analyze the vocal tract during the production of fricative consonants. These images were also used to build the associated 3D models and compute their volumes. This approach showed that, in general, the volumes measured for the voiceless consonants are smaller than the counterpart voiced consonants.

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Section: Measuring and Modelling Speech: A Reviewsupporting

confidence: 73%

3D Vocal Tract Reconstruction Using Magnetic Resonance Imaging Data to Study Fricative Consonant Production

Ventura

Freitas

Ramos

et al. 2015

Lecture Notes in Computational Vision and Biomechanics

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show abstract

“…Sometimes, in medical imaging monitoring of the healing process, or in monitoring tumor evolution, different sensors (with multimodal analysis) are used and images of the same scene are acquired by various sensors [22,27,37].…”

Section: Image Registration and Panoramic Image Stitching 221 Intrmentioning

confidence: 99%

Scars collaborative telediagnosis platform using adaptive image flow

Kassab

Lapayre

Aupet

et al. 2013

ICA

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Telemedicine has been developed to allow practitioners to remotely connect with patients and with other medical staff. We propose a new system (hardware and software), named DICODERM (COllaborative DIagnosis of DERMatosis), which makes it possible to monitor the evolution of scars after the excision of a tumorous dermatosis (like melanoma). The hardware part of this system is composed of a new optical innovative probe with which two types of images can be acquired simultaneously: anatomic with a white light image and functional with a fluorescence image (using autofluorescence from the protoporphyrin within the cancer cell). The software part is composed of two components: the image stitching component, and the collaborative/adaptive layer component. Our system creates a panoramic view of these scars obtained by stitching a sequence of small images. We conducted experiments for different image stitching algorithms to define the best solution. We also deployed a second component: a collaborative system layer which allows to remotely share images of scars and to adapt these images. We also made the system adaptive to communicate across different client platforms. We conducted experiments to compare the exchange of images with or without adaptation: these tests showed the efficiency of our layer.

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“…Many methods have been proposed for studying the speech production mechanism, including vocal tract segmentation from MRI sequences [4][5][6], discussing the tongue position for vowels [7][8][9][10], and the tongue motion patterns in speech production [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Extraction of tongue contour in real-time magnetic resonance imaging sequences

Zhang

Yang

Tao

et al. 2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Real-time magnetic resonance imaging (rtMRI) is becoming a practical tool in speech production research and language pathology observation. It is still a challenge to extract the tongue contour accurately in rtMRI sequences, since tongue is a soft tissue and often touches other organs such as lips and upper mandible. This paper proposes a novel semiautomatic tongue contour extraction method from rtMRI sequences. The initial boundary image is obtained by combined multi-directional Sobel operators in tongue movement region; then a boundary intensity map is constructed to find the most probable tongue contour points by searching for the optimal boundary route with Viterbi algorithm; finally the tongue contour is obtained using B-Spline approximation. The proposed method could obtain accurate tongue contour from rtMRI sequences, even in the cases that some parts of tongue touch other organs. Experiments demonstrate the robustness of the proposed method.

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Spatio-temporal resolution enhancement of vocal tract MRI sequences based on image registration

Cited by 16 publications

References 26 publications

3D Vocal Tract Reconstruction Using Magnetic Resonance Imaging Data to Study Fricative Consonant Production

3D Vocal Tract Reconstruction Using Magnetic Resonance Imaging Data to Study Fricative Consonant Production

Scars collaborative telediagnosis platform using adaptive image flow

Extraction of tongue contour in real-time magnetic resonance imaging sequences

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