Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics.

Diffusion-weighted imaging (DWI) and its numerical expression via apparent diffusion coefficient (ADC) values are commonly utilized in non-invasive assessment of various brain pathologies. Although numerous studies have confirmed that ADC values could be pathognomic for various ring-enhancing lesions (RELs), their true potential is yet to be exploited in full. The article was designed to introduce an image analysis method allowing REL recognition independently of either absolute ADC values or specifically defined regions of interest within the evaluated image.

Measurement-Based Domain Parameter Optimization in Electrical Impedance Tomography Imaging.

This paper discusses the optimization of domain parameters in electrical impedance tomography-based imaging. Precise image reconstruction requires accurate, well-correlated physical and numerical finite element method (FEM) models; thus, we employed the Nelder-Mead algorithm and a complete electrode model to evaluate the individual parameters, including the initial conductivity, electrode misplacement, and shape deformation. The optimization process was designed to calculate the parameters of the numerical model before the image reconstruction.

In vitro motor patterns and electrophysiological changes in patients with colonic diverticular disease.

Purpose: The underlying mechanism responsible for motility changes in colonic diverticular disease (DD) is still unknown. In the present study, our aim was to investigate the structural and in vitro motor changes in the sigmoid colon of patients with DD.

Methods: Muscle bath, microelectrodes and immunohistochemical techniques were performed with samples obtained from the left and sigmoid colon of patients with DD and compared with those of patients without DD.