Training Data Generation for U-Net Based MRI Image Segmentation using Level-Set Methods
Ş Ozan - Journal of Mathematical Sciences and Modelling, 2023 - dergipark.org.tr
Image segmentation has been a well-addressed problem in pattern recognition for the last
few decades. As a sub-problem of image segmentation, the background separation in …
few decades. As a sub-problem of image segmentation, the background separation in …
Multi-phase level set method for precise segmentation and correction of brain MRI
Medical image segmentation as an earlier application field in image segmentation is the key
technology of medical image analysis and is also a key point and difficulty in clinical …
technology of medical image analysis and is also a key point and difficulty in clinical …
A new level set model for unified medical image segmentation
X Shan, BN Li - TENCON 2015-2015 IEEE Region 10 …, 2015 - ieeexplore.ieee.org
Level set methods (LSMs) have been extensively investigated for medical image
segmentation. However, there are a few inherent drawbacks in common level set …
segmentation. However, there are a few inherent drawbacks in common level set …
A region-based level set formulation using machine learning approach in medical image segmentation
A new region-based active contour model in level set formulation is proposed to segment
medical images with poorly defined boundaries. From literature, it is observed that the …
medical images with poorly defined boundaries. From literature, it is observed that the …
Level set formulation based on edge and region information with application to accurate lesion segmentation of brain magnetic resonance images
Magnetic resonance images have great significance for doctors' analysis and diagnosis of
diseases. One difficulty in segmenting magnetic resonance images is associated with the …
diseases. One difficulty in segmenting magnetic resonance images is associated with the …
A unified level set framework utilizing parameter priors for medical image segmentation
Image segmentation plays an important role in many medical imaging systems, yet in
complex circumstances it remains an open problem. One of the main difficulties is the …
complex circumstances it remains an open problem. One of the main difficulties is the …
DRLSU-Net: Level set with U-Net for medical image segmentation
X Wang, J Liu, R Yang, Z Wu, L Sun, L Zou - Digital Signal Processing, 2025 - Elsevier
Convolutional neural networks (CNN) have been extensively utilized for image
segmentation tasks, with the U-Net architecture emerging as a classical model in medical …
segmentation tasks, with the U-Net architecture emerging as a classical model in medical …
Segmentation of noisy images using improved distance regularized level set evolution
P Yugander, GR Reddy - 2017 International Conference on …, 2017 - ieeexplore.ieee.org
In this paper, we propose a novel framework for the segmentation of noisy images by
incorporating the advantages of k-means clustering and distance regularized level set …
incorporating the advantages of k-means clustering and distance regularized level set …
A level set algorithm based on probabilistic statistics for MR image segmentation
J Liu, X Wei, Q Li, L Li - Intelligence Science and Big Data Engineering …, 2018 - Springer
MR image segmentation is of great importance in medical image application. MR images
have the characteristics of intensity inhomogeneities, strong background interference and …
have the characteristics of intensity inhomogeneities, strong background interference and …
Level set framework based on local scalable Gaussian distribution and adaptive-scale operator for accurate image segmentation and correction
Y Yang, H Ren, X Hou - Signal Processing: Image Communication, 2022 - Elsevier
Active contour model is a popular image segmentation method, but its current development
is still limited by the problem of uneven image intensity. This paper proposes a new active …
is still limited by the problem of uneven image intensity. This paper proposes a new active …