[Update on manual bronchial clearance techniques (adults and adolescents)]. / Mise au point sur les techniques manuelles de désencombrement bronchique (adultes et adolescents).

In adults and teenagers, airway clearance physiotherapy techniques (ACPT) are various and numerous. However, they for still awaiting scientific validation. Among ACPTs, Slow Expiration with the Glottis Opened in the Lateral Posture (ELTGOL), Autogenic Drainage (DA), and Active Cycling Breathing Technique (ACBT) present a Grade B level of evidence with weak recommendations. Even though these maneuvers are widely applied, precise description of chest physiotherapy (CP) is largely absent from the scientific literature; it is difficult to standardize its implementation and reproduce the results; scientific validation and faithful execution of the techniques are consequently problematic. In this paper, the authors aim to depict each of the three CP techniques as precisely as possible; with this in mind, graphic modeling of the different respiratory exercises is presented in such a way that they can be easily learned, applied and reproduced by physiotherapists.

Artificial intelligence for art investigation: Meeting the challenge of separating x-ray images of the Ghent Altarpiece.

X-ray images of polyptych wings, or other artworks painted on both sides of their support, contain in one image content from both paintings, making them difficult for experts to "read." To improve the utility of these x-ray images in studying these artworks, it is desirable to separate the content into two images, each pertaining to only one side. This is a difficult task for which previous approaches have been only partially successful. Deep neural network algorithms have recently achieved remarkable progress in a wide range of image analysis and other challenging tasks. We, therefore, propose a new self-supervised approach to this x-ray separation, leveraging an available convolutional neural network architecture; results obtained for details from the Adam and Eve panels of the Ghent Altarpiece spectacularly improve on previous attempts.

Independent component analysis for brain fMRI does not select for independence.

InfoMax and FastICA are the independent component analysis algorithms most used and apparently most effective for brain fMRI. We show that this is linked to their ability to handle effectively sparse components rather than independent components as such. The mathematical design of better analysis tools for brain fMRI should thus emphasize other mathematical characteristics than independence.

Image coding using wavelet transform.

A scheme for image compression that takes into account psychovisual features both in the space and frequency domains is proposed. This method involves two steps. First, a wavelet transform used in order to obtain a set of biorthogonal subclasses of images: the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal directions and maintains constant the number of pixels required to describe the image. Second, according to Shannon's rate distortion theory, the wavelet coefficients are vector quantized using a multiresolution codebook. To encode the wavelet coefficients, a noise shaping bit allocation procedure which assumes that details at high resolution are less visible to the human eye is proposed. In order to allow the receiver to recognize a picture as quickly as possible at minimum cost, a progressive transmission scheme is presented. It is shown that the wavelet transform is particularly well adapted to progressive transmission.