Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics
Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
[PDF][PDF] An overview of intelligent image segmentation using active contour models
The active contour model (ACM) approach in image segmentation is regarded as a research
hotspot in the area of computer vision, which is widely applied in different kinds of …
hotspot in the area of computer vision, which is widely applied in different kinds of …
A level set approach to image segmentation with intensity inhomogeneity
It is often a difficult task to accurately segment images with intensity inhomogeneity, because
most of representative algorithms are region-based that depend on intensity homogeneity of …
most of representative algorithms are region-based that depend on intensity homogeneity of …
Optic disk and cup segmentation from monocular color retinal images for glaucoma assessment
GD Joshi, J Sivaswamy… - IEEE transactions on …, 2011 - ieeexplore.ieee.org
Automatic retinal image analysis is emerging as an important screening tool for early
detection of eye diseases. Glaucoma is one of the most common causes of blindness. The …
detection of eye diseases. Glaucoma is one of the most common causes of blindness. The …
An active contour model driven by adaptive local pre-fitting energy function based on Jeffreys divergence for image segmentation
Active contour model (ACM) has been a competitive tool in image segmentation because of
its desired segmentation result and accuracy. Nevertheless, it may become unstable while …
its desired segmentation result and accuracy. Nevertheless, it may become unstable while …
Active contours driven by region-scalable fitting and optimized Laplacian of Gaussian energy for image segmentation
It had been known that the famous region scalable-fitting model can segment the images
with intensity inhomogeneity effectively, but it largely depends on the position of initial …
with intensity inhomogeneity effectively, but it largely depends on the position of initial …
A hybrid active contour model based on pre-fitting energy and adaptive functions for fast image segmentation
In this study, a hybrid active contour model driven by pre-fitting energy with an adaptive
edge indicator function and an adaptive sign function is proposed. The key idea of …
edge indicator function and an adaptive sign function is proposed. The key idea of …
Active contour model based on local Kullback–Leibler divergence for fast image segmentation
C Yang, G Weng, Y Chen - Engineering Applications of Artificial …, 2023 - Elsevier
The inhomogeneity of image intensity and noise are the main factors that affect the
segmentation results. To overcome these challenges, a new active contour model is …
segmentation results. To overcome these challenges, a new active contour model is …
Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer
Tertiary lymphoid structures (TLS) are ectopic aggregates of lymphoid cells in inflamed,
infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete …
infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete …
Active contour model based on local and global intensity information for medical image segmentation
This paper proposes a novel region-based active contour model in the level set formulation
for medical image segmentation. We define a unified fitting energy framework based on …
for medical image segmentation. We define a unified fitting energy framework based on …