Selective learning for sensing using shift-invariant spectrally stable undersampled networks.

The amount of data collected for sensing tasks in scientific computing is based on the Shannon-Nyquist sampling theorem proposed in the 1940s. Sensor data generation will surpass 73 trillion GB by 2025 as we increase the high-fidelity digitization of the physical world. Skyrocketing data infrastructure costs and time to maintain and compute on all this data are increasingly common.

COVID-19 radiograph prognosis using a deep CResNeXt network.

COVID-19 has caused an epidemic in the entire world and it is caused by the novel virus SARS-COV-2. In severe conditions, this virus can cause a critical lung infection or viral pneumonia. To administer the correct treatment to patients, COVID-19 testing is important for diagnosing and determining patients who are infected with COVID-19, as opposed to those infected with other bacterial or viral infections.

Paper-based dots and smartphone for detecting counterfeit country eggs.

Herein, we present for the first time, the employment of paper-based devices for rapidly differentiating original country eggs from the plain broiler eggs that have been coated with tea to appear as the former. The devices leverage two types of phenomena involving the phenols present in tea in precisely 5 min, namely precipitation, which produces a well-defined dark bluish precipitate on the surface of the counterfeit country eggs or tea-coated broiler eggs and de-coloration, wherein the dried layer of tea coating present on the surface of the dummy country eggs get dissolved, thereby revealing the white colour of the plain broiler egg shell. To reduce the subjectivity, a smartphone application 'Eggo' has been developed which is capable of detecting the spots produced by both the methods using mobile's camera.

Surface tension measurement of normal human blood samples by pendant drop method.

The surface tension of blood plays an important role not only in the birth and decompression sickness but also in other functionality of the organism. It also provides capillary action during blood flow process. In this article, a simple and low-cost device is designed and fabricated for measuring the surface tension of blood by pendant drop method.

Feature Extraction Based Machine Learning for Human Burn Diagnosis From Burn Images.

Burn is one of the serious public health problems. Usually, burn diagnoses are based on expert medical and clinical experience and it is necessary to have a medical or clinical expert to conduct an examination in restorative clinics or at emergency rooms in hospitals. But sometimes a patient may have a burn where there is no specialized facility available, and in such a case a computerized automatic burn assessment tool may aid diagnosis.

Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images.

This research presents an independent stand-alone graphical computational tool which functions as a neurological disease prediction framework for diagnosis of neurological disorders to assist neurologists or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images. The tool was built in collaboration with neurologists and neurosurgeons and many of the features are based on their feedback. This tool provides the user automatized functionality to perform automatic segmentation and extract the gray and white matter regions of patient brain image data using an algorithm called adapted fuzzy -means (FCM) membership-based clustering with preprocessing using the elliptical Hough transform and postprocessing using connected region analysis.

Image-based clustering and connected component labeling for rapid automated left and right ventricular endocardial volume extraction and segmentation in full cardiac cycle multi-frame MRI images of cardiac patients.

A rapid method for left and right ventricular endocardial volume segmentation and clinical cardiac parameter calculation from MRI images of cardiac patients is presented. The clinical motivation is providing cardiologists a tool for assessing the cardiac function in a patient through the left ventricular endocardial volume's ejection fraction. A new method combining adapted fuzzy membership-based c-means pixel clustering and connected regions component labeling is used for automatic segmentation of the left and right ventricular endocardial volumes.

Absorbable Suture as an Apical Matrix in Single Visit Apexification with Mineral Trioxide Aggregate.

Several procedures have been recommended to induce the root end barrier formation in teeth with open apices. Conventional treatment for such cases will require many appointments with an average duration of 12.9 months.

Diastema Closure in Anterior Teeth Using a Posterior Matrix.

Presence of diastema between anterior teeth is often considered an onerous esthetic problem. Various treatment modalities are available for diastema closure. However, not all diastemas can be treated the same in terms of modality or timing.

Four cuspal maxillary second premolar with single root and three root canals: Case report.

Traditional configuration of maxillary second premolars has been described to have two cusps, one root and one or two root canals. The endodontic literature reports considerable anatomic aberrations in the root canal morphology of maxillary second premolar but the literature available on the variation in cuspal anatomy and its relationship to the root canal anatomy is sparse. The purpose of this clinical report was to describe the root and root canal configuration of a maxillary second premolar with four cusps.

Automatic disease screening method using image processing for dried blood microfluidic drop stain pattern recognition.

This paper examines programmed automatic recognition of infection from samples of dried stains of micro-scale drops of patient blood. This technique has the upside of being low-cost and less-intrusive and not requiring puncturing the patient with a needle for drawing blood, which is especially critical for infants and the matured. It also does not require expensive pathological blood test laboratory equipment.

Multi-scale parameterisation of a myocardial perfusion model using whole-organ arterial networks.

A method to extract myocardial coronary permeabilities appropriate to parameterise a continuum porous perfusion model using the underlying anatomical vascular network is developed. Canine and porcine whole-heart discrete arterial models were extracted from high-resolution cryomicrotome vessel image stacks. Five parameterisation methods were considered that are primarily distinguished by the level of anatomical data used in the definition of the permeability and pressure-coupling fields.

Model-based vasculature extraction from optical fluorescence cryomicrotome images.

The aim of this study was to develop a novel method to reconstruct 3-D coronary vasculature from cryomicrotome images, comprised of two distinct sets of data-fluorescent microsphere beads and coronary vasculature. Fluorescent beads and cast injected into the vasculature were separately imaged with different filter settings to obtain the microsphere and vascular data, respectively. To extract the vascular anatomy, light scattering in the tissue was modelled using a point spread function (PSF).

Intramural spatial variation of optical tissue properties measured with fluorescence microsphere images of porcine cardiac tissue.

This proceeding studies the optical fluorescence images of a porcine heart filled with microspheres of two colors, carmine and red. A significant difference in the total optical tissue attenuation coefficient was observed between excitation and emission for both carmine (excitation - 13+/-4(1/mm) and emission - 9.4+/-3(1/mm)) and red (excitation -29+/-5(1/mm) and emission - 25+/-5(1/mm)), indicating that optical tissue properties can change significantly for a small change in light wavelength.