State-of-the-art methods for brain tissue segmentation: A review
Brain tissue segmentation is one of the most sought after research areas in medical image
processing. It provides detailed quantitative brain analysis for accurate disease diagnosis …
processing. It provides detailed quantitative brain analysis for accurate disease diagnosis …
On the binding problem in artificial neural networks
Contemporary neural networks still fall short of human-level generalization, which extends
far beyond our direct experiences. In this paper, we argue that the underlying cause for this …
far beyond our direct experiences. In this paper, we argue that the underlying cause for this …
The variational approximation for Bayesian inference
The influence of this Thomas Bayes' work was immense. It was from here that" Bayesian"
ideas first spread through the mathematical world, as Bayes's own article was ignored until …
ideas first spread through the mathematical world, as Bayes's own article was ignored until …
Automatic visual detection system of railway surface defects with curvature filter and improved Gaussian mixture model
Rails are among the most important components of railway transportation, and real-time
defects detection of the railway is an important and challenging task because of intensity …
defects detection of the railway is an important and challenging task because of intensity …
Expectation–maximization-driven geodesic active contour with overlap resolution (emagacor): Application to lymphocyte segmentation on breast cancer …
The presence of lymphocytic infiltration (LI) has been correlated with nodal metastasis and
tumor recurrence in HER2+ breast cancer (BC). The ability to automatically detect and …
tumor recurrence in HER2+ breast cancer (BC). The ability to automatically detect and …
Fast and robust spatially constrained Gaussian mixture model for image segmentation
In this paper, a new mixture model for image segmentation is presented. We propose a new
way to incorporate spatial information between neighboring pixels into the Gaussian mixture …
way to incorporate spatial information between neighboring pixels into the Gaussian mixture …
Neural network approach to background modeling for video object segmentation
This paper presents a novel background modeling and subtraction approach for video
object segmentation. A neural network (NN) architecture is proposed to form an …
object segmentation. A neural network (NN) architecture is proposed to form an …
DM-RIS: Deep multimodel rail inspection system with improved MRF-GMM and CNN
Rail inspection system (RIS) remains an emergent instrumentation for railway transportation,
with its capacity of measuring surface defect on steel rail. However, detecting technique and …
with its capacity of measuring surface defect on steel rail. However, detecting technique and …
A class-adaptive spatially variant mixture model for image segmentation
C Nikou, NP Galatsanos… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
We propose a new approach for image segmentation based on a hierarchical and spatially
variant mixture model. According to this model, the pixel labels are random variables and a …
variant mixture model. According to this model, the pixel labels are random variables and a …
Robust spatially constrained fuzzy c-means algorithm for brain MR image segmentation
Objective Accurate brain tissue segmentation from magnetic resonance (MR) images is an
essential step in quantitative brain image analysis, and hence has attracted extensive …
essential step in quantitative brain image analysis, and hence has attracted extensive …