Suchergebnisse - "3D convolutional autoencoders"

A 3D Sparse Autoencoder for Fully Automated Quality Control of Affine Registrations in Big Data Brain MRI Studies von Thadikemalla, Venkata Sainath Gupta, Focke, Niels K., Tummala, Sudhakar

“… This paper presents a fully automated pipeline using a sparse convolutional autoencoder for quality control (QC) of affine registrations in large-scale …”
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Alzheimer's disease classification based on combination of multi-model convolutional networks von Fan Li, Danni Cheng, Manhua Liu

“… Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. It brings increasingly …”
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Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder von Zhao, Yu, Dong, Qinglin, Chen, Hanbo, Iraji, Armin, Li, Yujie, Makkie, Milad, Kou, Zhifeng, Liu, Tianming

“… •A new deep 3D convolutional autoencoder to model brain network maps.•Derived fine-granularity functional brain network atlases …”
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Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images von Li, Frank, Choi, Jiwoong, Zou, Chunrui, Newell, John D., Comellas, Alejandro P., Lee, Chang Hyun, Ko, Hongseok, Barr, R. Graham, Bleecker, Eugene R., Cooper, Christopher B., Abtin, Fereidoun, Barjaktarevic, Igor, Couper, David, Han, MeiLan, Hansel, Nadia N., Kanner, Richard E., Paine, Robert, Kazerooni, Ella A., Martinez, Fernando J., O’Neal, Wanda, Rennard, Stephen I., Smith, Benjamin M., Woodruff, Prescott G., Hoffman, Eric A., Lin, Ching-Long

“… We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC …”
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Simulated four-dimensional CT for markerless tumor tracking using a deep learning network with multi-task learning von Mori, Shinichiro, Hirai, Ryusuke, Sakata, Yukinobu

“… (each field representing one-ninth of the respiratory cycle) from each CT dataset based on a 3D convolutional autoencoder with shortcut connections using deformable image registration …”
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Three-Dimensional Convolutional Autoencoder Extracts Features of Structural Brain Images With a “Diagnostic Label-Free” Approach: Application to Schizophrenia Datasets von Yamaguchi, Hiroyuki, Hashimoto, Yuki, Sugihara, Genichi, Miyata, Jun, Murai, Toshiya, Takahashi, Hidehiko, Honda, Manabu, Hishimoto, Akitoyo, Yamashita, Yuichi

“… The purpose of this study was to investigate the efficacy of a 3D convolutional autoencoder (3D-CAE …”
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Behavior Score-Embedded Brain Encoder Network for Improved Classification of Alzheimer Disease Using Resting State fMRI von Hsieh, Wan-Ting, Lefort-Besnard, Jeremy, Yang, Hao-Chun, Kuo, Li-Wei, Lee, Chi-Chun

“… BSEN is based on a 3D convolutional autoencoder structure with contrastive loss jointly optimized using behavior scores from Mini-Mental State Examination (MMSE …”
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Deep Learning of Lung Diseases on Computed Tomography Images von Li, Frank

“… This research is a collection of three papers on the use of deep learning to detect and classify lung diseases or lung injuries using a CAE-FC model or a …”
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Learning Local Feature Descriptions in 3D Ultrasound von Wulff, Daniel, Hagenah, Jannis, Ipsen, Svenja, Ernst, Floris

“… Tools for automatic image analysis are gaining importance in the clinical workflow, ranging from time-saving tools in diagnostics to real-time methods in …”
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Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning von Onga, Yuto, Fujiyama, Shingo, Arai, Hayato, Chayama, Yusuke, Iyatomi, Hitoshi, Oishi, Kenichi

“… ). In DDCML, we introduce deep metric learning to a 3D convolutional autoencoder (CAE). Our proposed DDCML scheme achieves a high dimensional compression rate (4096:1 …”
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Three-dimensional convolutional autoencoder extracts features of structural brain images with a diagnostic label-free approach: Application to schizophrenia datasets von Yamaguchi, Hiroyuki, Hashimoto, Yuki, Sugihara, Genichi, Miyata, Jun, Murai, Toshiya, Takahashi, Hidehiko, Honda, Manabu, Hishimoto, Akitoyo, Yamashita, Yuichi

“… The purpose of this study was to investigate the efficacy of a 3D convolutional autoencoder (CAE …”
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Behavior Score-Embedded Brain Encoder Network for Improved Classification of Alzheimer Disease Using Resting State fMRI von Wan-Ting, Hsieh, Lefort-Besnard, Jeremy, Hao-Chun, Yang, Li-Wei, Kuo, Chi-Chun, Lee

“… BSEN is based on a 3D convolutional autoencoder structure with contrastive loss jointly optimized using behavior scores from MiniMental State Examination (MMSE …”
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Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning von Onga, Yuto, Fujiyama, Shingo, Arai, Hayato, Chayama, Yusuke, Iyatomi, Hitoshi, Oishi, Kenichi

“… ). In DDCML, we introduce deep metric learning to a 3D convolutional autoencoder (CAE). Our proposed DDCML scheme achieves a high dimensional compression rate (4096:1 …”
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