Fuzzy region-based active contour driven by global and local fitting energy for image segmentation
J Fang, H Liu, J Liu, H Zhou, L Zhang, H Liu - Applied Soft Computing, 2021 - Elsevier
This paper presents a novel global and local fuzzy image fitting (GLFIF) based active
contour model for image segmentation. First, we design two fitted images: global fuzzy fitted …
contour model for image segmentation. First, we design two fitted images: global fuzzy fitted …
An IoMT-based melanoma lesion segmentation using conditional generative adversarial networks
Currently, Internet of medical things-based technologies provide a foundation for remote
data collection and medical assistance for various diseases. Along with developments in …
data collection and medical assistance for various diseases. Along with developments in …
SLDCNet: Skin lesion detection and classification using full resolution convolutional network‐based deep learning CNN with transfer learning
Background Skin cancer is one of the life threating diseases in the world. So, millions of lives
can be saved by early detection of skin cancer. In addition, automating the computer‐aided …
can be saved by early detection of skin cancer. In addition, automating the computer‐aided …
A fuzzy C-means clustering algorithm based on spatial context model for image segmentation
J Xu, T Zhao, G Feng, M Ni, S Ou - International Journal of Fuzzy Systems, 2021 - Springer
Abstract An improved Fuzzy C-Means (FCM) algorithm, which is called Reliability-based
Spatial context Fuzzy C-Means (RSFCM), is proposed for image segmentation in this paper …
Spatial context Fuzzy C-Means (RSFCM), is proposed for image segmentation in this paper …
A survey on regional level set image segmentation models based on the energy functional similarity measure
L Zou, LT Song, T Weise, XF Wang, QJ Huang, R Deng… - Neurocomputing, 2021 - Elsevier
Image segmentation is an important field of computer vision and has attracted significant
research attention in the recent years. In this paper, we provide a survey of regional level set …
research attention in the recent years. In this paper, we provide a survey of regional level set …
Robust FCM clustering algorithm with combined spatial constraint and membership matrix local information for brain MRI segmentation
This paper presents a robust fuzzy clustering algorithm for the segmentation of brain tissues
in magnetic resonance imaging (MRI). The proposed method incorporates context-aware …
in magnetic resonance imaging (MRI). The proposed method incorporates context-aware …
[PDF][PDF] 基于上下文模糊C 均值聚类的图像分割算法
徐金东， 赵甜雨， 冯国政， 欧世峰 - 电子与信息学报, 2021 - jeit.ac.cn
基于上下文模糊C均值聚类的图像分割算法Image Segmentation Algorithm Based on Context
Fuzzy C-Means Clustering Page 1 基于上下文模糊C均值聚类的图像分割算法 徐金东*① 赵甜 …
Fuzzy C-Means Clustering Page 1 基于上下文模糊C均值聚类的图像分割算法 徐金东*① 赵甜 …
A novel coarse-to-Fine Sea-land segmentation technique based on Superpixel fuzzy C-means clustering and modified Chan-Vese model
The sea-land segmentation for optical remote sensing images (RSIs) has a valuable role in
water resources and coastal zones management. However, it is challenging because optical …
water resources and coastal zones management. However, it is challenging because optical …
Inhomogeneous image segmentation using hybrid active contours model with application to breast tumor detection
The most fatal and frequent cancer amongst women is breast cancer. Mammography
provides timely detection of lumps and masses in breast tissue, but effective diagnosis …
provides timely detection of lumps and masses in breast tissue, but effective diagnosis …
NeuronAlg: an innovative neuronal computational model for immunofluorescence image segmentation
G Giacopelli, M Migliore, D Tegolo - Sensors, 2023 - mdpi.com
Background: Image analysis applications in digital pathology include various methods for
segmenting regions of interest. Their identification is one of the most complex steps and …
segmenting regions of interest. Their identification is one of the most complex steps and …