Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model
Sign Up to like & getrecommendations! Published in 2019 at "Medical Physics"
DOI: 10.1002/mp.13268
Abstract: PURPOSE Due to the low contrast, blurry boundaries, and large amount of shadows in breast ultrasound (BUS) images, automatic tumor segmentation remains a challenging task. Deep learning provides a solution to this problem, since it… read more here.
Keywords: network; segmentation; fully convolutional; tumor segmentation ... See more keywords
A Fully Convolutional Network (FCN) based Automated Ischemic Stroke Segment Method using Chemical Exchange Saturation Transfer Imaging.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.15483
Abstract: BACKGROUND Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration. However, the accurate segmentation of pH-altered regions remains difficult due to… read more here.
Keywords: fully convolutional; chemical exchange; segmentation; exchange saturation ... See more keywords
Deep-segmentation of plantar pressure images incorporating fully convolutional neural networks
Sign Up to like & getrecommendations! Published in 2020 at "Biocybernetics and Biomedical Engineering"
DOI: 10.1016/j.bbe.2020.01.004
Abstract: Abstract Comfort shoe-last design relies on the key points of last curvature. Traditional plantar pressure image segmentation methods are limited to their local and global minimization issues. In this work, an improved fully convolutional networks… read more here.
Keywords: plantar pressure; deep segmentation; segmentation; fully convolutional ... See more keywords
Fully Convolutional Neural Network: A solution to infer animal behaviours from multi-sensor data
Sign Up to like & getrecommendations! Published in 2021 at "Ecological Modelling"
DOI: 10.1016/j.ecolmodel.2021.109555
Abstract: Abstract Animal-attached accelerometers have been widely used to monitor species that are difficult to observe, alongside the use of machine learning to identify behaviours from the obtained sequences. Artificial neural networks are powerful supervised learning… read more here.
Keywords: fully convolutional; neural network; animal; ecology ... See more keywords
Direct left-ventricular global longitudinal strain (GLS) computation with a fully convolutional network.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of biomechanics"
DOI: 10.1016/j.jbiomech.2021.110878
Abstract: This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Encoding with Stimulated Echoes… read more here.
Keywords: fully convolutional; longitudinal strain; left ventricular; convolutional network ... See more keywords
Multi-class multimodal semantic segmentation with an improved 3D fully convolutional networks
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.11.103
Abstract: Abstract Semantic segmentation is an important but challenging task in the field of medical image analysis. Automatic labeling for different anatomical structures can be useful for disease diagnosis, treatment planning and development/degeneration evaluation. However, due… read more here.
Keywords: fully convolutional; convolutional networks; semantic segmentation; segmentation ... See more keywords
Multi-Scale and Single-Scale Fully Convolutional Networks for Sound Event Detection
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.09.038
Abstract: Abstract Among various Sound Event Detection (SED) systems, Recurrent Neural Networks (RNN), such as long short-term memory unit and gated recurrent unit, is used to capture temporal dependencies, but it is confined in its length… read more here.
Keywords: detection; convolutional networks; temporal dependencies; fully convolutional ... See more keywords
Imagery Creation based on Autonomic System for Finite Element by using Fully Convolutional Network
Sign Up to like & getrecommendations! Published in 2020 at "Procedia Manufacturing"
DOI: 10.1016/j.promfg.2020.02.059
Abstract: Abstract For applications in Industry 4.0, a system that can analyze the deformation and stress of a target object from an image acquired by a smartphone or tablet is proposed in this paper. The process… read more here.
Keywords: finite element; target object; system; fully convolutional ... See more keywords
Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping
Sign Up to like & getrecommendations! Published in 2019 at "Remote Sensing of Environment"
DOI: 10.1016/j.rse.2019.111253
Abstract: Accurate spatial information of agricultural fields in smallholder farms is important for providing actionable information to farmers, managers, and policymakers. Very High Resolution (VHR) satellite images can capture such information. However, the automated delineation of… read more here.
Keywords: agricultural fields; using fully; fully convolutional; satellite images ... See more keywords
Prediction of elastic stresses in porous materials using fully convolutional networks
Sign Up to like & getrecommendations! Published in 2021 at "Scripta Materialia"
DOI: 10.1016/j.scriptamat.2021.113805
Abstract: Abstract Machine learning (ML) models enable exploration of vast structural space faster than the traditional methods, such as finite element method (FEM). This makes ML models suitable for stochastic fracture problems in brittle porous materials.… read more here.
Keywords: prediction elastic; fully convolutional; convolutional networks; porous materials ... See more keywords
Fully convolutional neural nets in-the-wild
Sign Up to like & getrecommendations! Published in 2020 at "Remote Sensing Letters"
DOI: 10.1080/2150704x.2020.1821120
Abstract: ABSTRACT The ground breaking performance of fully convolutional neural nets (FCNs) for semantic segmentation tasks has yet to be achieved for landcover classification, partly because a lack of suitable training data. Here the FCN8 model… read more here.
Keywords: classification; fully convolutional; convolutional neural; nets wild ... See more keywords