Automatic segmentation of vocal tract articulators in real-time magnetic resonance imaging

BACKGROUND AND OBJECTIVES

The characterization of the vocal tract geometry during speech interests various research topics, including speech production modeling, motor control analysis, and speech therapy design. Real-time MRI is a reliable and non-invasive tool for this purpose. In most cases, it is necessary to know the contours of the individual articulators from the glottis to the lips. Several techniques have been proposed for segmenting vocal tract articulators, but most are limited to specific applications. Moreover, they often do not provide individualized contours for all soft-tissue articulators in a multi-speaker configuration.

METHODS

A Mask R-CNN network was trained to detect and segment the vocal tract articulator contours in two real-time MRI (RT-MRI) datasets with speech recordings of multiple speakers. Two post-processing algorithms were then proposed to convert the network's outputs into geometrical curves. Nine articulators were considered: the two lips, tongue, soft palate, pharynx, arytenoid cartilage, epiglottis, thyroid cartilage, and vocal folds. A leave-one-out cross-validation protocol was used to evaluate inter-speaker generalization. The evaluation metrics were the point-to-closest-point distance and the Jaccard index (for articulators annotated as closed contours).

RESULTS

The proposed method accurately segmented the vocal tract articulators, with an average root mean square point-to-closest-point distance of less than 2.2mm for all the articulators in the leave-one-out cross-validation setting. The minimum P2CPRMS was 0.91mm for the upper lip, and the maximum was 2.18mm for the tongue. The Jaccard indices for the thyroid cartilage and vocal folds were 0.60 and 0.61, respectively. Additionally, the method adapted to a new subject with only ten annotated samples.

CONCLUSIONS

Our research introduced a method for individually segmenting nine non-rigid vocal tract articulators in real-time MRI movies. The software is openly available as an installable package to the speech community. It is designed to develop speech applications and clinical and non-clinical research in fields that require vocal tract geometry, such as speech, singing, and human beatboxing.

Feasibility of online non-rigid motion correction for high-resolution supine breast MRI

PURPOSE

Conventional breast MRI is performed in the prone position with a dedicated coil. This allows high-resolution images without breast motion, but the patient position is inconsistent with that of other breast imaging modalities or interventions. Supine breast MRI may be an interesting alternative, but respiratory motion becomes an issue. Motion correction methods have typically been performed offline, for instance, the corrected images were not directly accessible from the scanner console. In this work, we seek to show the feasibility of a fast, online, motion-corrected reconstruction integrated into the clinical workflow.

METHODS

Fully sampled T2 -weighted (T2 w) and accelerated T1 -weighted (T1 w) breast supine MR images were acquired during free-breathing and were reconstructed using a non-rigid motion correction technique (generalized reconstruction by inversion of coupled systems). Online reconstruction was implemented using a dedicated system combining the MR raw data and respiratory signals from an external motion sensor. Reconstruction parameters were optimized on a parallel computing platform, and image quality was assessed by objective metrics and by radiologist scoring.

RESULTS

Online reconstruction time was 2 to 2.5 min. The metrics and the scores related to the motion artifacts significantly improved for both T2 w and T1 w sequences. The overall quality of T2 w images was approaching that of the prone images, whereas the quality of T1 w images remained significantly lower.

CONCLUSION

The proposed online algorithm allows a noticeable reduction of motion artifacts and an improvement of the diagnostic quality for supine breast imaging with a clinically acceptable reconstruction time. These findings serve as a starting point for further development aimed at improving the quality of T1 w images.

Evaluation of Image Quality of Motion-Corrected Supine Breast MRI

Breast MRI is the most performant modality for breast cancer diagnosis and could be widespread in the future. The gold standard breast MRI is performed in the prone position, but comfort and correlation with surgery or biopsy positioning can be problematic, while supine MRI could be an interesting alternative. In this work, we evaluated the image quality of T2-weighted supine breast MRI in healthy volunteers after online correction of respiratory motion artifacts compared to standard vendor's reconstruction and to standard prone MRI. T2-weighted images were acquired in the prone and free-breathing supine position in 10 volunteers. Two types of reconstructions were evaluated for supine acquisitions: the standard vendor's reconstruction and an online version of a nonrigid motion correction technique (generalized reconstruction by inversion of coupled system). Image quality criteria, including overall quality, sharpness, uniformity, and different types of artifacts, were assessed and scored by 2 radiologists in a randomized fashion. Interobserver agreement was verified by Weighted Cohen's Kappa calculation and a comparison between the different acquisitions was made by Wilcoxon signed-rank test. Generalized Reconstruction by Inversion of Coupled Systems (GRICS) reconstruction method significantly increased image quality in comparison to the standard reconstruction of supine acquisition. It allows a comparable quality, slightly lower than the gold standard prone MRI in T2-weighted images but it needs to be assessed with more patients and with target lesions before it can be used in clinical practice.

Super-Resolved Dynamic 3D Reconstruction of the Vocal Tract during Natural Speech

MRI is the gold standard modality for speech imaging. However, it remains relatively slow, which complicates imaging of fast movements. Thus, an MRI of the vocal tract is often performed in 2D. While 3D MRI provides more information, the quality of such images is often insufficient. The goal of this study was to test the applicability of super-resolution algorithms for dynamic vocal tract MRI. In total, 25 sagittal slices of 8 mm with an in-plane resolution of 1.6 × 1.6 mm2 were acquired consecutively using a highly-undersampled radial 2D FLASH sequence. The volunteers were reading a text in French with two different protocols. The slices were aligned using the simultaneously recorded sound. The super-resolution strategy was used to reconstruct 1.6 × 1.6 × 1.6 mm3 isotropic volumes. The resulting images were less sharp than the native 2D images but demonstrated a higher signal-to-noise ratio. It was also shown that the super-resolution allows for eliminating inconsistencies leading to regular transitions between the slices. Additionally, it was demonstrated that using visual stimuli and shorter text fragments improves the inter-slice consistency and the super-resolved image sharpness. Therefore, with a correct speech task choice, the proposed method allows for the reconstruction of high-quality dynamic 3D volumes of the vocal tract during natural speech.

Methodology for quantitative evaluation of mandibular condyles motion symmetricity from real-time MRI in the axial plane

Diagnosis of temporomandibular disorders is currently based on clinical examination and static MRI. Real-time MRI enables tracking of condylar motion and, thus, evaluation of their motion symmetricity (which could be associated with temporomandibular joint disorders). The purpose of this work is to propose an acquisition protocol, an image processing approach, and a set of parameters enabling objective assessment of motion asymmetry; to check the reliability and find the limitations of the approach, and to verify if the automatically calculated parameters are associated with the motion symmetricity. A rapid radial FLASH sequence was used to acquire a dynamic set of axial images for 10 subjects. One more subject was involved to estimate the dependence of the motion parameters on the slice placement. The images were segmented with a semi-automatic approach based on U-Net convolutional neural network, and the condyles' mass centers were projected on the mid-sagittal axis. Resulting projection curves were used for the extraction of various motion parameters including latency, velocity peak delay, and maximal displacement between the right and the left condyle. These automatically calculated parameters were compared with the physicians' scores. The proposed segmentation approach allowed a reliable center of mass tracking. Latency and velocity peak delay were found to be invariant to the slice position, and maximal displacement difference considerably varied. The automatically calculated parameters demonstrated a significant correlation with the experts' scores. The proposed acquisition and data processing protocol enables the automatizable extraction of quantitative parameters that characterize the symmetricity of condylar motion.

A hardware and software system for MRI applications requiring external device data

PURPOSE

Numerous MRI applications require data from external devices. Such devices are often independent of the MRI system, so synchronizing these data with the MRI data is often tedious and limited to offline use. In this work, a hardware and software system is proposed for acquiring data from external devices during MR imaging, for use online (in real-time) or offline.

METHODS

The hardware includes a set of external devices - electrocardiography (ECG) devices, respiration sensors, microphone, electronics of the MR system etc. - using various channels for data transmission (analog, digital, optical fibers), all connected to a server through a universal serial bus (USB) hub. The software is based on a flexible client-server architecture, allowing real-time processing pipelines to be configured and executed. Communication protocols and data formats are proposed, in particular for transferring the external device data to an open-source reconstruction software (Gadgetron), for online image reconstruction using external physiological data. The system performance is evaluated in terms of accuracy of the recorded signals and delays involved in the real-time processing tasks. Its flexibility is shown with various applications.

RESULTS

The real-time system had low delays and jitters (on the order of 1 ms). Example MRI applications using external devices included: prospectively gated cardiac cine imaging, multi-modal acquisition of the vocal tract (image, sound, and respiration) and online image reconstruction with nonrigid motion correction.

CONCLUSION

The performance of the system and its versatile architecture make it suitable for a wide range of MRI applications requiring online or offline use of external device data.

Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers

The study of articulatory gestures has a wide spectrum of applications, notably in speech production and recognition. Sets of phonemes, as well as their articulation, are language-specific; however, existing MRI databases mostly include English speakers. In our present work, we introduce a dataset acquired with MRI from 10 healthy native French speakers. A corpus consisting of synthetic sentences was used to ensure a good coverage of the French phonetic context. A real-time MRI technology with temporal resolution of 20 ms was used to acquire vocal tract images of the participants speaking. The sound was recorded simultaneously with MRI, denoised and temporally aligned with the images. The speech was transcribed to obtain phoneme-wise segmentation of sound. We also acquired static 3D MR images for a wide list of French phonemes. In addition, we include annotations of spontaneous swallowing.

Measurement(s)	Vocal tract images • Speech
Technology Type(s)	Magnetic Resonance Imaging • Microphone Device
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16404453

Intracellular Detection and Localization of Nanoparticles by Refractive Index Measurement

The measuring of nanoparticle toxicity faces an important limitation since it is based on metrics exposure, the concentration at which cells are exposed instead the true concentration inside the cells. In vitro studies of nanomaterials would benefit from the direct measuring of the true intracellular dose of nanoparticles. The objective of the present study was to state whether the intracellular detection of nanodiamonds is possible by measuring the refractive index. Based on optical diffraction tomography of treated live cells, the results show that unlabeled nanoparticles can be detected and localized inside cells. The results were confirmed by fluorescence measurements. Optical diffraction tomography paves the way to measuring the true intracellular concentrations and the localization of nanoparticles which will improve the dose-response paradigm of pharmacology and toxicology in the field of nanomaterials.

Silicon-Based Optoelectronic Tongue for Label-Free and Nonspecific Recognition of Vegetable Oils

A special electronic tongue system based on photoelectric measurements on Si-Si/SiN X sensitive structures is reported. The sensing approach is based on measuring of minority carrier lifetime in silicon-based substrates using microwave-detected photoconductance decay. This inexpensive and environmentally friendly combinatorial electronic sensing platform is able to create characteristic electronic fingerprints of liquids, detect, and recognize them. In particular, an application of the optoelectronic tongue for recognition of vegetable oils and their mixtures is described.