C&EN

Toward Digital Staining using Imaging Mass Spectrometry and Random Forests

Heidelberg Collaboratory for Image Processing (HCI), Interdisciplinary Center for Scientific Computing (IWR), University of Heidelberg, Speyerer Strasse 6, 69115 Heidelberg, Germany, FOM-AMOLF, ...
IEEE

Sub-Markov Random Walk for Image Segmentation

Abstract: A novel sub-Markov random walk (subRW) algorithm with label prior is proposed for seeded image segmentation, which can be interpreted as a traditional random walker on a graph with added ...
JSTOR Daily

THE EXTREMES OF RANDOM WALKS IN RANDOM SCENERIES

Advances in Applied Probability, Vol. 41, No. 2 (JUNE 2009), pp. 452-468 (17 pages) In this article we analyse the behaviour of the extremes of a random walk in a random scenery. The random walk is ...
Scientific Research Publishing

Single Tooth Segmentation on Panoramic X-Rays Using End-to-End Deep Neural Networks ()

1 Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China. 2 Landing Artificial Intelligence Center for Pathological Diagnosis, Wuhan University, Wuhan, China.
Frontiers

Quantitative analysis of chest MRI images for benign malignant diagnosis of pulmonary solid nodules

In this study, we developed and validated machine learning (ML) models by combining radiomic features extracted from magnetic resonance imaging (MRI) with clinicopathological factors to assess ...
C&EN

Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

† Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States ‡ The Ragon Institute of MGH, MIT, and Harvard, ...
IEEE

Hierarchical Random Walker Segmentation for Large Volumetric Biomedical Images

Abstract: The random walker method for image segmentation is a popular tool for semi-automatic image segmentation, especially in the biomedical field. However, its linear asymptotic run time and ...
Nature

Automatic segmentation of inner ear on CT-scan using auto-context convolutional neural network

Temporal bone CT-scan is a prerequisite in most surgical procedures concerning the ear such as cochlear implants. The 3D vision of inner ear structures is crucial for diagnostic and surgical ...
Frontiers

Accurate Neuronal Soma Segmentation Using 3D Multi-Task Learning U-Shaped Fully Convolutional Neural Networks

Neuronal soma segmentation is a crucial step for the quantitative analysis of neuronal morphology. Automated neuronal soma segmentation methods have opened up the opportunity to improve the ...