High resolution automated labeling of the hippocampus and amygdala using a 3D convolutional neural network trained on whole brain 700 μm isotropic 7T MP2RAGE MRI
Sign Up to like & getrecommendations! Published in 2021 at "Human Brain Mapping"
DOI: 10.1002/hbm.25348
Abstract: Image labeling using convolutional neural networks (CNNs) are a template‐free alternative to traditional morphometric techniques. We trained a 3D deep CNN to label the hippocampus and amygdala on whole brain 700 μm isotropic 3D MP2RAGE MRI… read more here.
Keywords: mp2rage mri; hippocampus; hippocampus amygdala; cnn based ... See more keywords
Automatic detection of contouring errors using convolutional neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Medical Physics"
DOI: 10.1002/mp.13814
Abstract: Purpose To develop a head and neck normal structures autocontouring tool that could be used to automatically detect the errors in autocontours from a clinically validated autocontouring tool. Methods An autocontouring tool based on convolutional… read more here.
Keywords: macs; autocontouring tool; tool; convolutional neural ... See more keywords
Convolutional neural network-based model observer for signal known statistically task in breast tomosynthesis images.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16395
Abstract: BACKGROUND Since human observer studies are resource-intensive, mathematical model observers are frequently used to assess task-based image quality. The most common implementation of these model observers assume that the signal information is exactly known. However,… read more here.
Keywords: based model; model; cnn based; model observer ... See more keywords
CNN‐based fully automatic wrist cartilage volume quantification in MR images: A comparative analysis between different CNN architectures
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29671
Abstract: Automatic measurement of wrist cartilage volume in MR images. read more here.
Keywords: cnn based; cartilage volume; wrist cartilage;
CNN-based gender classification in near-infrared periocular images
Sign Up to like & getrecommendations! Published in 2018 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-018-0722-3
Abstract: Periocular region has emerged as a key biometric trait with potential applications in the forensics domain. In this paper, we explore two convolutional neural network (CNN)-based approaches for gender classification using near-infrared images of the… read more here.
Keywords: classification; near infrared; cnn based; periocular images ... See more keywords
A CNN-based computational algorithm for nonlinear image diffusion problem
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09077-0
Abstract: In the past, several partial differential equations (PDEs) based methods have been widely studied in image denoising. While solving these methods numerically, some parameters need to be chosen manually. This paper proposes a cellular neural… read more here.
Keywords: image; diffusion; computational algorithm; algorithm nonlinear ... See more keywords
CNN-based single object detection and tracking in videos and its application to drone detection
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09924-0
Abstract: This paper presents convolutional neural network (CNN)-based single object detection and tracking algorithms. CNN-based object detection methods are directly applicable to static images, but not to videos. On the other hand, model-free visual object tracking… read more here.
Keywords: object detection; detection; single object; detection tracking ... See more keywords
Deep CNN Based Lmser and Strengths of Two Built-In Dualities
Sign Up to like & getrecommendations! Published in 2020 at "Neural Processing Letters"
DOI: 10.1007/s11063-020-10341-5
Abstract: Least mean square error reconstruction for the self-organizing network (Lmser) was proposed in 1991, featured by a bidirectional architecture with several built-in natures. In this paper, we developed Lmser into CNN based Lmser (CLmser), highlighted… read more here.
Keywords: strengths two; lmser strengths; based lmser; deep cnn ... See more keywords
CNN-Based Deep Learning Model for Solar Wind Forecasting
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DOI: 10.1007/s11207-021-01874-6
Abstract: This article implements a Convolutional Neural Network (CNN)-based deep learning model for solar-wind prediction. Images from the Atmospheric Imaging Assembly (AIA) at 193\.A wavelength are used for training. Solar-wind speed is taken from the Advanced… read more here.
Keywords: wind; deep learning; model; cnn based ... See more keywords
Robust optimization of the locations and types of multiple wells using CNN based proxy models
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Petroleum Science and Engineering"
DOI: 10.1016/j.petrol.2020.107424
Abstract: Abstract For the cost-effective optimization of well locations and types under geologic uncertainty, proxy modeling or surrogate modeling of reservoir simulation is required. Recently, a machine learning algorithm has been widely applied to predict reservoir… read more here.
Keywords: proxy models; types multiple; based proxy; optimization ... See more keywords
Exploring the Influence of Input Feature Space on CNN‐Based Geomorphic Feature Extraction From Digital Terrain Data
Sign Up to like & getrecommendations! Published in 2023 at "Earth and Space Science"
DOI: 10.1029/2023ea002845
Abstract: Many studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way… read more here.
Keywords: cnn based; space; feature; input feature ... See more keywords