Image Segmentation of Brain MRI Based on LTriDP and Superpixels of Improved SLIC
Brain Sciences, 2020 Non-uniform gray distribution and blurred edges often result in bias during the superpixel segmentation of medical images of magnetic resonance imaging (MRI).
Yu Wang, Qi Qi, Xuanjing Shen
doaj +1 more source
SAR Image Segmentation Based on Fisher Vector Superpixel Generation and Label Revision
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 This article addresses the problem of superpixel-bases segmentation of synthetic aperture radar (SAR) images. Most superpixel segmentation methods have difficulties in segmenting adjacent regions with similar gray values, due to only considering spatial ...
Ronghua Shang +5 more
doaj +1 more source
Superpixel Segmentation Using Gaussian Mixture Model [PDF]
IEEE Transactions on Image Processing, 2018 Superpixel segmentation algorithms are to partition an image into perceptually coherence atomic regions by assigning every pixel a superpixel label. Those algorithms have been wildly used as a preprocessing step in computer vision works, as they can enormously reduce the number of entries of subsequent algorithms.
Zhihua Ban, Jianguo Liu, Li Cao
openaire +4 more sources
Stereo Superpixel Segmentation via Decoupled Dynamic Spatial-Embedding Fusion Network [PDF]
IEEE transactions on multimedia, 2022 Stereo superpixel segmentation aims at grouping the discretizing pixels into perceptual regions through left and right views more collaboratively and efficiently.
Hua Li +5 more
semanticscholar +1 more source
Video Segmentation with Superpixels [PDF]
, 2013 Due to its importance, video segmentation has regained interest recently. However, there is no common agreement about the necessary ingredients for best performance. This work contributes a thorough analysis of various within- and between-frame affinities suitable for video segmentation.
Galasso F, Cipolla R, Schiele B
openaire +3 more sources
Superpixel Segmentation Algorithm by Spatial Constrained Density Clustering
Journal of Harbin University of Science and Technology, 2020 The superpixel segmentation is an important pre-processing step in computer image processing. Thetraditional superpixel segmentation algorithm based on density clustering is better for boundary processing，but the resulting superpixel shape is irregular ...
HAN Jian-hui, TANG Jun-chao
doaj +1 more source
DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation [PDF]
, 2015 Automatic organ segmentation is an important yet challenging problem for medical image analysis. The pancreas is an abdominal organ with very high anatomical variability.
Farag, Amal +6 more
core +1 more source
Tumor localization in tissue microarrays using rotation invariant superpixel pyramids [PDF]
, 2015 Tumor localization is an important component of histopathology image analysis; it has yet to be reliably automated for breast cancer histopathology. This paper investigates the use of superpixel classification to localize tumor regions.
Akbar, Shazia +3 more
core +3 more sources
Automated detection of extended sources in radio maps: progress from the SCORPIO survey [PDF]
, 2016 Automated source extraction and parameterization represents a crucial challenge for the next-generation radio interferometer surveys, such as those performed with the Square Kilometre Array (SKA) and its precursors.
Buemi, C. S. +9 more
core +2 more sources
Background Subtraction Based on Random Superpixels Under Multiple Scales for Video Analytics
IEEE Access, 2018 Background subtraction is a fundamental problem of computer vision, which is usually the first step of video analytics to extract the interesting region.
Weitao Fang +5 more
doaj +1 more source