Deep Learning Model With Convolutional Neural Network for Detecting and Segmenting Hepatocellular Carcinoma in CT: A Preliminary Study.

Introduction Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world. Early detection and accurate diagnosis of HCC play an important role in patient management. This study aimed to develop a convolutional neural network-based model to identify and segment HCC lesions utilizing dynamic contrast agent-enhanced computed tomography (CT).

Kinetics of adhesion of the oral bacterium Streptococcus sanguis CH3 to polymers with different surface free energies.

The kinetics of adhesion of Streptococcus sanguis CH3 from suspension to polymers with different surface free energies were studied by using three bacterial concentrations (2.5 X 10(7), 2.5 X 10(8), and 2.

Adhesion of Streptococcus sanguis CH3 to polymers with different surface free energies.

The adhesion of the oral bacterium Streptococcus sanguis CH3 to various polymeric surfaces with surface free energies (gamma s) ranging from 22 to 141 erg cm-2 was investigated. Suspensions containing nine different bacterial concentrations (2.5 X 10(7) to 2.