LungNeuralNet We demonstrated that the CNNs, including U-Net and Mask R-CNN, are instrumental to provide: efficient evaluation of pathological lung lesions. detailed characterization of the normal lung histology. precise detection and classification for BALF cells. Overall, these advanced methods allow improved efficiency and quantification of lung cytology and histopathology. Applications of U-Net like architectures The convolutional neural network architecture used in this project was inspired by U-Net and dual frame U-Net with added transfer learning from pre-trained models in keras (keras-applications). Lung Pathology After training on 14 image pairs, the neural network is able to reach >90% accuracy (dice coefficient) in identifying lung parenchymal region and >60% for severe inflammation in the lung in the validation set.

Research Article Parenchymal Airspace Profiling: Sensitive Quantification and Characterization of Lung Structure Evaluating Parenchymal Destruction. Xiao R, Goldklang MP, D’Armiento JM. Am J Respir Cell Mol Biol. 2016 Nov;55(5):708-715. Software Download & Screenshots Download link for Windows Update Logs Under Binarization Settings->Global Thresholding, relative threshold settings were changed to find a specific percentile from the histogram, which is more accurate than +/- an integer based on mean brightness value. Under General Settings, “crop ratio” was added because finding the correct threshold for large images can be time-consuming. This crop ratio will be applied after resizing and only keep the center portion of your image (0.

This article offers a sample of basic Markdown syntax that can be used in Hugo content files, also it shows whether basic HTML elements are decorated with CSS in a Hugo theme.