As one of the most important tasks in biomedical imaging, image segmentation provides the
foundation for quantitative reasoning and diagnostic techniques. A large variety of different …

The purpose of this study is to investigate multiregion graph cut image partitioning via kernel
map** of the image data. The image data is transformed implicitly by a kernel function so …

In this paper, we present a CNN-based fully unsupervised method for motion segmentation
from optical flow. We assume that the input optical flow can be represented as a piecewise …

Motion segmentation is one of the main tasks in computer vision and is relevant for many
applications. The optical flow (OF) is the input generally used to segment every frame of a …

A novel optical flow estimation process based on a spatio-temporal model with varying
coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical …

This study investigates level set multiphase image segmentation by kernel map** and
piecewise constant modeling of the image data thereof. A kernel function maps implicitly the …

In current level set image segmentation methods, the number of regions is assumed to
known beforehand. As a result, it remains constant during the optimization of the objective …

Artificial intelligence (AI) scholars and mediciners have reported AI systems that accurately
detect medical imaging and COVID‐19 in chest images. However, the robustness of these …

Current algorithmic approaches for piecewise affine motion estimation are based on
alternating motion segmentation and estimation. We propose a new method to estimate …

This study investigates variational image segmentation with an original data term, referred to
as statistical overlap prior, which measures the conformity of overlap between the …