AIMC Topic: Image Processing, Computer-Assisted

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Machine Learning Interface for Medical Image Analysis.

Journal of digital imaging
TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision dataset...

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mec...

Learning the Personalized Intransitive Preferences of Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Most of the previous studies on the user preferences assume that there is a personal transitive preference ranking of the consumable media like images. For example, the transitivity of preferences is one of the most important assumptions in the recom...

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

Journal of digital imaging
Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image pr...

Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification.

Bioinformatics (Oxford, England)
SUMMARY: State-of-the-art light and electron microscopes are capable of acquiring large image datasets, but quantitatively evaluating the data often involves manually annotating structures of interest. This process is time-consuming and often a major...

Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms.

Bioinformatics (Oxford, England)
MOTIVATION: Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful tool for analyzing structures of macromolecular complexes and their spati...

Label-free detection of aggregated platelets in blood by machine-learning-aided optofluidic time-stretch microscopy.

Lab on a chip
According to WHO, about 10 million new cases of thrombotic disorders are diagnosed worldwide every year. Thrombotic disorders, including atherothrombosis (the leading cause of death in the US and Europe), are induced by occlusion of blood vessels, du...

Deep Learning in Mammography: Diagnostic Accuracy of a Multipurpose Image Analysis Software in the Detection of Breast Cancer.

Investigative radiology
OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mammography d...

A multi-scale convolutional neural network for phenotyping high-content cellular images.

Bioinformatics (Oxford, England)
MOTIVATION: Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustm...