Variational level set image segmentation model coupled with kernel distance function
Journal of Algorithms & Computational Technology, 2020 One of the crucial challenges in the area of image segmentation is intensity inhomogeneity. For most of the region-based models, it is not easy to completely segment images having severe intensity inhomogeneity and complex structure, as they rely on ...
Noor Badshah, Ali Ahmad, Fazli Rehman
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An active contour model for the segmentation of images with intensity inhomogeneities and bias field estimation. [PDF]
PLoS ONE, 2015 Intensity inhomogeneity causes many difficulties in image segmentation and the understanding of magnetic resonance (MR) images. Bias correction is an important method for addressing the intensity inhomogeneity of MR images before quantitative analysis ...
Chencheng Huang, Li Zeng
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ACTIVE CONTOUR MODEL USING FRACTIONAL SYNC WAVE FUNCTION FOR MEDICAL IMAGE SEGMENTATION
Asia-Pacific Journal of Information Technology and Multimedia, 2016 Intensity inhomogeneity occurs when pixels in medical images overlap due to anomalies in medical imaging devices. These anomalies lead to difficult medical image segmentation.
Norshaliza Kamaruddin
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Relaxation of intense inhomogeneous charged beams [PDF]
Physics of Plasmas, 2009 This work analyzes the dynamics of inhomogeneous, magnetically focused high intensity beams of charged particles. Initial inhomogeneities lead to density waves propagating transversely in the beam core, and the presence of transverse waves eventually results in particle scattering.
R. P. Nunes +4 more
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A variational level set model with kernel metric induced local image fitting energy
IET Image Processing, 2022 Active contour based methods are effective models for image segmentation. However, they always suffer from the limited performance due to the presence of noise and intensity inhomogeneity.
Junxiao Yan +3 more
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A novel fuzzy energy based level set method for medical image segmentation
Cogent Engineering, 2018 Segmentation is a very important step in the field of image processing. Noise and intensity inhomogeneity make challenging the segmentation of images, especially for medical images. Fuzzy C-means (FCM) clustering is one of the most widely used methods in
Mahipal Singh Choudhry, Rajiv Kapoor
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IEEE Access, 2020 Local region-based active contour models (ACMs) can effectively segment images corrupted by intensity inhomogeneity, however, they always converge to local minimum and are sensitive to the initial position of contour.
Hongli Lv, Fangjian Zhang, Renfang Wang
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A Novel Hybrid Active Contour Model for Intracranial Tuberculosis MRI Segmentation Applications
IEEE Access, 2020 This paper proposes an improved region-based active contour model for segmenting magnetic resonance imaging (MRI) images of brain tuberculosis by combining a global energy fitting term and a local energy fitting term.
Yuzhen Cao +7 more
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Label-Distribution Learning-Embedded Active Contour Model for Breast Tumor Segmentation
IEEE Access, 2019 Tumor segmentation is the foundation of breast ultrasound image analysis. However, intensity inhomogeneity occurred in ultrasound images results in the ambiguous segmentation.
Yongjian Wu +7 more
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Inhomogeneity of Macroseismic Intensities in Italy and Consequences for Macroseismic Magnitude Estimation [PDF]
Seismological Research Letters, 2021 AbstractWe show that macroseismic intensities assessed in Italy in the last decade are not homogeneous with those of the previous periods. This is partly related to the recent adoption of the European Macroseismic Scale (EMS) in place of the Mercalli–Cancani–Sieberg (MCS) scale used up to about one decade ago. The underestimation of EMS with respect to
Gianfranco, Vannucci +2 more
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