Results 151 to 160 of about 6,546,628 (369)
Systematic review of image segmentation using complex networks [PDF]
arXivThis review presents various image segmentation methods using complex networks. Image segmentation is one of the important steps in image analysis as it helps analyze and understand complex images. At first, it has been tried to classify complex networks based on how it being used in image segmentation.
arxiv
Automated image detection and segmentation in blood smears [PDF]
, 1992 Steven S.S. Poon +2 more
openalex +1 more source
, 2019 Realistic editing of photographs requires careful treatment of color mixtures that commonly occur in natural scenes. These color mixtures are typically modeled using soft selection of objects or scene colors. Hence, accurate representation of these soft transitions between image regions is essential for high-quality image editing and compositing ...
openaire +3 more sources
DRINet for Medical Image Segmentation
IEEE Transactions on Medical Imaging, 2018 Convolutional neural networks (CNNs) have revolutionized medical image analysis over the past few years. The U-Net architecture is one of the most well-known CNN architectures for semantic segmentation and has achieved remarkable successes in many different medical image segmentation applications. The U-Net architecture consists of standard convolution
Liang Chen +5 more
openaire +5 more sources
Multiple sclerosis clinical decision support system based on projection to reference datasets
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1863-1873, December 2022., 2022 Abstract Objective Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on‐demand computational power to address the challenges of dynamically managing MS. Methods A phase 3 clinical trial data (NCT00906399) were used to contextualize the medication efficacy of peg‐interferon beta‐1a vs ...
Chadia Ed‐driouch +13 more
wiley +1 more source
Nonlinear analog networks for image smoothing and segmentation [PDF]
, 1991 Andrew Lumsdaine +2 more
openalex +1 more source
A potential biomarker of cognitive impairment: The olfactory dysfunction and its genes expression
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1884-1897, December 2022., 2022 Abstract Objective Accumulation evidence has reported that olfactory impairment may be an essential clinical marker and predictor of mild cognitive impairment or Alzheimer's disease. Method Participants were enrolled in the population‐based, prospective study in Fuxin county, Liaoning province, China between 2019 and 2021.
Jiayi Song +11 more
wiley +1 more source
Ain Shams Engineering Journal, 2018 Segmentation is one of the important steps for image analysis. Multilevel thresholding image segmentation was more popular in image segmentation. Otsu and Kapur based methods are most popular for multilevel threshold image segmentation.
Sowjanya Kotte +2 more
doaj
A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging [PDF]
arXiv, 2015 In this work it is proposed a medical image segmentation pipeline for accurate bone segmentation from CT imaging. It is a two-step methodology, with a pre-segmentation step and a segmentation refinement step. First, the user performs a rough segmenting of the desired region of interest.
arxiv
Clinical utility of cerebrospinal fluid biomarkers measured by LUMIPULSE® system
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1898-1909, December 2022., 2022 Abstract Objectives Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are well‐established in research settings, but their use in routine clinical practice remains a largely unexploited potential. Here, we examined the relationship between CSF biomarkers, measured by a fully automated immunoassay platform, and brain β‐amyloid (Aβ ...
Hisashi Nojima +9 more
wiley +1 more source