Ultrasound-induced Gas Release from Contrast Agent Microbubbles

We investigated gas release from two hard-shelled ultrasound contrast agents by subjecting them to high-mechanical index (MI) ultrasound and simultaneously capturing high-speed photographs. At an insonifying frequency of 1.7 MHz, a larger percentage of contrast bubbles is seen to crack than at 0.5 MHz. Most of the released gas bubbles have equilibrium diameters between 1.25 and 1.75 /spl mu/m. Their disappearance was observed optically. Free gas bubbles have equilibrium diameters smaller than the bubbles from which they have been released. Coalescence may account for the long dissolution times acoustically observed and published in previous studies. After sonic cracking, the cracked bubbles stay acoustically active

DASS-CARE 2.0: Blockchain-Based Healthcare Framework for Collaborative Diagnosis in CIoMT Ecosystem

Due to current Covid-19 pandemic, several countries enforce lock-down to prevent pandemic outspread. Hence, the mode of delivery of health services shall change as physical visits are not allowed. As such, the need of tele-medicine service and remote diagnosis have become a necessity. To provide reliable, safe, secure, and sustainable tele-medicine consultancy services, the supporting IT infrastructure need to be transformed. Therefore, it is necessary to use new generation of information technologies such as loT, Blockchain, and cloud computing to transform the traditional medical systems to smart healthcare systems. In this paper, we propose a proof of concept (PoC) of an ameliorated version of our DASS-CARE framework that supports decentralized, accessible, scalable, and secure access to healthcare services based on Internet of Medical things (IoMT) and Artificial Intelligence (AI). In this paper, we propose DASS-CARE 2.0 that offers more medical services including: (a) the real time health monitoring, (b) the collaborative and secure access to medical records, (c) the storage of medical history diagnosis and prescriptions, and (d)the patient\u27s discharge and bills\u27 payments. The paper concludes with future changes to the framework that can furnish further services

Noninvasive microbubble-based pressure measurements: a simulation study

This paper describes a noninvasive method to measure local hydrostatic pressures in fluid filled cavities. The method is based on the disappearance time of a gas bubble, as the disappearance time is related to the hydrostatic pressure. When a bubble shrinks, its response to ultrasound changes. From this response, the disappearance time, and with it the hydrostatic pressure, can be determined. We investigated the applicability of the gases Ar, C3F8, Kr, N2, Ne, and SF6, based on their diffusive properties. For pressure measurements with a limited duration, e.g. 150 ms, Kr and Ar bubbles are most suitable, since they are most sensitive to pressure change. If there is also a limitation to bubble size, e.g. a maximum diameter of 6 lm, SF6 is most suitable. We present improvements of a method that correlates the duration of the decay of the fundamental ultrasound response to the hydrostatic overpressure. We propose to correlate the duration until subharmonic occurrence in combination with its decay, to hydrostatic overpressure, since the subharmonic decays more rapidly than the fundamental response. For a dissolving Ar gas bubble with an initial diameter of 14 lm, the overpressure can be determined 4 times as precise from the decay of the subharmonic response as from the decay of the fundamental response. Overpressures as small as 11 mmHg may be discriminated with this method

Pathological Cluster Identification by Unsupervised Analysis in 3,822 UK Biobank Cardiac MRIs

International audienceWe perform unsupervised analysis of image-derived shape and motion features extracted from 3,822 cardiac Magnetic resonance imaging (MRIs) of the UK Biobank. First, with a feature extraction method previously published based on deep learning models, we extract from each case 9 feature values characterizing both the cardiac shape and motion. Second, a feature selection is performed to remove highly correlated feature pairs. Third, clustering is carried out using a Gaussian mixture model on the selected features. After analysis, we identify 2 small clusters that probably correspond to 2 pathological categories. Further confirmation using a trained classification model and dimensionality reduction tools is carried out to support this finding. Moreover, we examine the differences between the other large clusters and compare our measures with the ground truth

Curve smoothing and matching

We present a new approach to the problem of matching 3D curves . The approach has an algorithmic complexity sublinear with the number of models, and can operate in the presence of noise and partial occlusions . Our method buids upon the seminal work of [27, 28], where curves are first smoothed using B-splines, with matching based on hashing using curvature and torsion measures . However, we introduce two enhancements * Ce travail a été en partie financé par Digital Equipment Corporation .We present a new approach to the problem of matching 3D curves . The approach has an algorithmic complexity sublinear with the number of models, and can operate in the presence of noise and partial occlusions . Our method buids upon the seminal work of [27, 28], where curves are first smoothed using B-splines, with matching based on hashing using curvature and torsion measures . However, we introduce two enhancements * Ce travail a été en partie financé par Digital Equipment Corporation . We present a new approach to the problem of matching 3D curves . The approach has an algorithmic complexity sublinear with the number of models, and can operate in the presence of noise and partial occlusions . Our method buids upon the seminal work of [27, 28], where curves are first smoothed using B-splines, with matching based on hashing using curvature and torsion measures . However, we introduce two enhancements * Ce travail a été en partie financé par Digital Equipment Corporation . we make use of non-uniform B-spline approximations, which permits us to better retain information at high curvature locations . The spline approximations are controlled (i.e ., regularized) by making use of normal vectors to the surface in 3-D on which the curves lie, and by an explicit minimization of a bending energy . These measures allow a more accurate estimation of position, curvatue, torsion and Frénet frames along the curve ; • the computational complexity of the recognition process is considerably decreased with explicit use of the Frénet frame for hypotheses generation . As opposed to previous approaches, the method better copes with partial occlusion . Moreover, following a statistical study of the curvature and torsion covariances, we optimize the hash table discretization and discover improved invariants for recognition, différent than the torsion measure. Finally, knowledge of invariant uncertainties is used to compute an optimal global transformation using an extended Kalman filter . We present experimental results using synthetic data and also using characteristic curves extracted front 3D medical images .Nous présentons une solution originale au problème de la reconnaissance et du recalage d'une courbe gauche discrète. La spécificité du problème est la nécessité de conserver une faible complexité algorithmique en présence d'un très grand nombre de modèles, d'être robuste au bruit et aux occultations partielles. Notre approche est une continuation logique des travaux de [27, 28] fondés sur un lissage des points par une courbe régulière puis par une reconnaissance à l'aide d'une table d'indexation mais présente deux innovations importantes: . pour une détermination plus fiable du modèle et de ses dérivées, les points discrets sont lissés par des splines en utilisant un critère d'erreur mixte et une distribution non uniforme de nœuds fondée sur la courbure locale et une régularisation exploitant la connaissance de la normale à la surface sur laquelle la courbe est inscrite et minimisant explicitement la variation de la courbure..

Low back pain, the stiffness of the sacroiliac joint: A new method using ultrasound

Abnormal biomechanical properties of the sacroiliac joints are believed to be related to low back and pelvic pain. Presently, physiotherapists judge the condition of the sacroiliac joints by function and provocation tests, and palpation. No objective measuring device is available. Research is ongoing to identify the biomechanical properties of the sacroiliac joints from the dynamic behaviour of the pelvic bones. A new concept based on ultrasound (US) for the measurement of bone vibration is under investigation. The objective of this study was to validate this concept on a physical model and to assess the applicability in vivo. A model consisting of a piezo shaker covered by a layer of US transmission gel (representing bone and soft tissue) has been used. A packet of US detection signals is directed onto the shaker and correlation-based processing is used to estimate the difference in time-of-flight of their echoes. These variations of time are used to compute the displacement of the shaker at each pulse reflection. To assess the validity of our US technique, we compared the obtained measurements with the readings of the built-in strain gauge sensor. The experimental procedure has been tested on a volunteer where low-frequency excitation was provided through the ilium and vibration detected on the sacrum and ilia. The results demonstrated that the correlation-based approach is capable of reproducing the piezo shaker displacements with high accuracy (± 7%). Vibration amplitudes from 0.25 μm to 3 μm could be measured. The US technique was able to detect bone vibration in vivo. In conclusion, the principle based on US waves can be used to develop a new measurement tool, instrumental in studying the relation between the biomechanical properties of the sacroiliac joints and low back pain

Automatically building morphometric anatomical atlases from 3D medical images : Application to a skull atlas

In this article, we present a method for building entirely automatically a morphometric anatomical atlas from 3D medical image s acquired by CT-Scan or MR . We detail each step of the method, including the non-rigid registration algorithm, 3D lines averaging , and statistical analysis processes . We apply the method to obtain a quantitative atlas of crest lines of the skull . Finally, we use the resulting atlas to study a craniofacia l disease : we show how we can obtain qualitative and quantitative results by contrasting a skull affected by a deformation of th e mandible with the atlas .Dans cet article, nous présentons une méthode pour construire de manière automatique des atlas anatomiques morphométriques à partir d'images médicales tridimensionnelles obtenues par scanographie ou imagerie par résonance magnétique. Nous en détaillons les différentes étapes, en particulier les algorithmes de mise en correspondance non-rigide, de moyenne et d'analyse statistique de lignes caractéristiques tridimensionnelles. Nous appliquons la méthode à la construction d'un atlas morphométrique des lignes de crête du crâne. Nous montrons alors comment la comparaison automatique entre l'atlas et un crâne présentant une déformation mandibulaire permet d'obtenir des résultats qualitatifs et quantitatifs utilisables par un médecin