Coronavirus (COVID-19) detection from chest radiology images using convolutional neural networks.

Coronavirus disease (Covid-19) has been spreading all over the world and its diagnosis is attracting more research every moment. It is need of the hour to develop automated methods, which could detect this disease at its early stage, in a non-invasive way and within lesser time. Currently, medical specialists are analyzing Computed Tomography (CT), X-Ray, and Ultrasound (US) images or conducting Polymerase Chain Reaction (PCR) for its confirmation on manual basis.

Paclitaxel loaded magnetic nanocomposites with folate modified chitosan/carboxymethyl surface; a vehicle for imaging and targeted drug delivery.

In this study, Paclitaxel (PTX) containing, bovine serum albumin (BSA) nanoparticles were fabricated via a simple approach. Folic acid (FA) was conjugated to chitosan (CS)/carboxymethyl cellulose (CMC) through an esterification reaction to produce BSA-CS-FA or BSA-CMC-FA conjugates. NiFeO noncore (NFs) and PTX were loaded through a heat treatment and by a diffusion process.

Diagnostic value of apparent diffusion coefficient for the accurate assessment and differentiation of intracranial meningiomas.

Background: Diffusion-weighted imaging (DWI) along with the calculation of apparent diffusion coefficient (ADC), is a novel, non-invasive, and reliable technique of choice for accurate assessment and for the treatment planning of different types of brain tumors. It is more advantageous in the distinction and differentiation of benign from malignant meningiomas on the basis of ADC values.

Purpose: To investigate the utility of DW magnetic resonance imaging (MRI), and to compare the apparent diffusion coefficient (ADC) obtained at two b-values for an authentic and preoperative characterization of meningiomas.