Incorporating artificial intelligence in portable infrared thermal imaging for the diagnosis and staging of nonalcoholic fatty liver disease.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Thermal imaging combined with advanced image-processing and machine learning analysis accurately classified disease status in a study on mice; this study aimed to develop this tool for humans. This prospective study included 46 patients who underwent liver biopsy.

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders.

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g.

Non-ionizing measurement and quantification of bell-shaped chests in spinal muscular atrophy: a pilot study.

Background: Spinal Muscular Atrophy (SMA) is manifested by deformation of the chest wall, including a bell-shaped chest. We determined the ability of a novel non-ionizing, non-volitional method to measure and quantify bell-shaped chests in SMA.

Methods: A 3D depth camera and a chest x-ray (CXR) were used to capture chest images in 14 SMA patients and 28 controls.

Classification of hand and wrist movements via surface electromyogram using the random convolutional kernels transform.

Prosthetic devices are vital for enhancing personal autonomy and the quality of life for amputees. However, the rejection rate for electric upper-limb prostheses remains high at around 30%, often due to issues like functionality, control, reliability, and cost. Thus, developing reliable, robust, and cost-effective human-machine interfaces is crucial for user acceptance.

Smartphone-based detection of COVID-19 and associated pneumonia using thermal imaging and a transfer learning algorithm.

COVID-19-related pneumonia is typically diagnosed using chest x-ray or computed tomography images. However, these techniques can only be used in hospitals. In contrast, thermal cameras are portable, inexpensive devices that can be connected to smartphones.

Morphological features of the photoplethysmographic signal: a new approach to characterize the microcirculatory response to photobiomodulation.

Advanced analysis of the morphological features of the photoplethysmographic (PPG) waveform may provide greater understanding of mechanisms of action of photobiomodulation (PBM). Photobiomodulation is a non-ionizing, red to near-infrared irradiation shown to induce peripheral vasodilatation, promote wound healing, and reduce pain. Using laser Doppler flowmetry combined with thermal imaging we found previously in a clinical study that PBM stimulates microcirculatory blood flow and that baseline palm skin temperature determines, at least in part, why some individuals respond favorably to PBM while others do not.

Automated processing of thermal imaging to detect COVID-19.

Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms. We captured thermal images of the backs of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones.

Assessment of blood distribution in response to post-surgical steal syndrome: A novel technique based on Thermo-Anatomical Segmentation.

The distal ischemic steal syndrome (ISS) is a complication following the construction of an arteriovenous (A-V) access for hemodialysis. The ability to non-invasively monitor changes in skin microcirculation improves both the diagnosis and treatment of vascular diseases. In this study, we propose a novel technique for evaluating the palms' blood distribution following arteriovenous access, based on thermal imaging.

Automated thermal imaging for the detection of fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) comprises a spectrum of progressive liver pathologies, ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. A liver biopsy is currently required to stratify high-risk patients, and predicting the degree of liver inflammation and fibrosis using non-invasive tests remains challenging. Here, we sought to develop a novel, cost-effective screening tool for NAFLD based on thermal imaging.

Microcirculatory Response to Photobiomodulation-Why Some Respond and Others Do Not: A Randomized Controlled Study.

Background And Objectives: Photobiomodulation (PBM), a non-ionizing, non-thermal irradiation, used clinically to accelerate wound healing and inhibit pain, was previously shown to increase blood flow. However, some individuals respond to PBM, but others do not. The purpose of this study was to investigate factors affecting this patient-specific response using advanced, noninvasive methods for monitoring microcirculatory activity.

Non-invasive thermal imaging of cardiac remodeling in mice.

Thermal infrared imaging has been suggested as a non-invasive alternative to monitor physiological processes and disease. However, the use of this technique to image internal organs, such as the heart, has not yet been investigated. We sought to determine the ability of our novel thermal image-processing algorithm to detect structural and functional changes in a mouse model of hypertension and cardiac remodeling.

The response of peripheral microcirculation to gravity-induced changes.

Background: The peripheral microcirculation supplies fresh blood to the small blood vessels, providing oxygen and nutrients to the tissues, removing waste, and maintaining normal homeostatic conditions. The goal of this study was to characterize the response of the peripheral microcirculation, in terms of blood flow and tissue oxygenation variables, to gravity-induced changes.

Methods: The study included 20 healthy volunteers and the experiment involved monitoring central and peripheral variables with the right hand positioned at different heights.

Noninvasive monitoring of peripheral microcirculatory hemodynamics under varying degrees of hypoxia.

The effect of hypoxia on skin blood flow was examined in anesthetized rabbits during induction of various levels of hypoxia. Peripheral perfusion and oxygenation were monitoring using a combined system (LPT) composed of a laser Doppler flowmeter (LDF), a photoplatysmograph (PPG), and a transcutaneous oxygen tension monitor (tc-PO2). Central blood parameters (PaO2, HCO3(-), SaO2, pH, and lactate) were measured concomitantly throughout the experiment.

Diffusion methods for aligning medical datasets: location prediction in CT scan images.

The purpose of this study is to introduce diffusion methods as a tool to label CT scan images according to their position in the human body. A comparative study of different methods based on a k-NN search is carried out and we propose a new, simple and efficient way of applying diffusion techniques that is able to give better location forecasts than methods that can be considered the current state-of-the-art.

Nonlinear intrinsic variables and state reconstruction in multiscale simulations.

Finding informative low-dimensional descriptions of high-dimensional simulation data (like the ones arising in molecular dynamics or kinetic Monte Carlo simulations of physical and chemical processes) is crucial to understanding physical phenomena, and can also dramatically assist in accelerating the simulations themselves. In this paper, we discuss and illustrate the use of nonlinear intrinsic variables (NIV) in the mining of high-dimensional multiscale simulation data. In particular, we focus on the way NIV allows us to functionally merge different simulation ensembles, and different partial observations of these ensembles, as well as to infer variables not explicitly measured.

Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures.

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories.

Edge-enhancement postprocessing using artificial dissipation.

We present a method to enhance, by postprocessing, the performance of gradient-based edge detectors. It improves the performance of the edge detector by adding terms which are similar to the artificial dissipation that appear in the numerical solution of hyperbolic PDEs. This term is added to the output of the edge detector.