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Published in 2019 at "Medical physics"
DOI: 10.1002/mp.13735
Abstract: PURPOSE Automatic and accurate 3D segmentation of liver with severe diseases from computed tomography (CT) images is a challenging task. Fully convolutional networks (FCN) have emerged as powerful tools for automatic semantic segmentation, with multiple…
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Keywords:
contour models;
network;
segmentation;
liver ... See more keywords
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Published in 2020 at "Machine Vision and Applications"
DOI: 10.1007/s00138-020-01083-4
Abstract: Traditional level set-based image segmentation method has to solve the level set evolution equation which is the Euler–Lagrange equation of the energy functional defined on the image domain. Solving level set evolution equation is very…
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Keywords:
piecewise constant;
active contour;
model;
constant active ... See more keywords
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Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-07806-8
Abstract: Video imagery based crowd analysis has become a topic of great interest for public safety at the venues of mass gathering events. This paper presents a novel approach to detect anomalous scene in high density…
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Keywords:
approach active;
crowd;
oriented tracklets;
tracklets approach ... See more keywords
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Published in 2018 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-017-1134-3
Abstract: Image segmentation is to divide an image into different parts or extract some interested objects. Active contour model and fuzzy clustering are two widely used segmentation methods, which have been integrated into an effective model…
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Keywords:
segmentation;
local segmentation;
model;
active contour ... See more keywords
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Published in 2019 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-018-0978-x
Abstract: Medical image segmentation has been widely used in clinical practice. It is an important basis for medical experts to diagnose the disease. However, weak edges and intensity inhomogeneity (Niu et al. in 2nd IEEE international…
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Keywords:
active contour;
segmentation;
constraint factor;
contour ... See more keywords
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Published in 2017 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2017.07.005
Abstract: The diagnostic of the vestibular neuritis (VN) presents many difficulties to traditional assessment methods This paper deals with a fully automatic VN diagnostic system based on nystagmus parameter estimation using a pupil detection algorithm. A…
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Keywords:
estimation;
parameter estimation;
vestibular neuritis;
active contour ... See more keywords
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Published in 2017 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2017.02.020
Abstract: BACKGROUND AND OBJECTIVES Automatic delineation of the myocardium in echocardiography can assist radiologists to diagnosis heart problems. However, it is still challenging to distinguish myocardium from other tissue due to a low signal-to-noise ratio, low…
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Keywords:
contour model;
active contour;
method;
myocardium ... See more keywords
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Published in 2021 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2020.105914
Abstract: In cardiology, ultrasound is often used to diagnose heart disease associated with myocardial infarction. This study aims to develop robust segmentation techniques for segmenting the left ventricle (LV) in ultrasound images to check myocardium movement…
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Keywords:
left ventricle;
segmentation;
convolutional neural;
active contour ... See more keywords
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Published in 2020 at "Optik"
DOI: 10.1016/j.ijleo.2019.163667
Abstract: Abstract In order to solve the problem that the region-based active contour model is sensitive to the initial contour position, the convergence is poor, and the active contour model can not obtain good segmentation results…
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Keywords:
energy;
segmentation;
model;
active contour ... See more keywords
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Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.11.003
Abstract: Abstract Active contour model (ACM) is able to obtain sub-pixel precision segmentation and has been widely employed in biomedical image analysis and video segmentation. Existing region-based ACMs (RACM) without enough prior constraints, however, easily fail when segmenting…
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Keywords:
frequency;
segmentation;
model;
active contour ... See more keywords
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Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.06.019
Abstract: Abstract Active contour model (ACM) is an effective method for image segmentation that has been widely used in various research fields. For images with severe intensity inhomogeneity, most existing ACMs show a poor segmentation performance.…
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Keywords:
active contour;
model;
bias correction;
contour model ... See more keywords