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Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation
Multimodal positron emission tomography-computed tomography (PET-CT) is ...
07/29/2020 ∙ by Xiaohang Fu, et al. ∙
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Semi-supervised estimation of event temporal length for cell event detection
Cell event detection in cell videos is essential for monitoring of cellu...
09/22/2019 ∙ by Ha Tran Hong Phan, et al. ∙
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Unsupervised Feature Learning with K-means and An Ensemble of Deep Convolutional Neural Networks for Medical Image Classification
Medical image analysis using supervised deep learning methods remains pr...
06/07/2019 ∙ by Euijoon Ahn, et al. ∙
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Unsupervised Deep Transfer Feature Learning for Medical Image Classification
The accuracy and robustness of image classification with supervised deep...
03/15/2019 ∙ by Euijoon Ahn, et al. ∙
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Co-Learning Feature Fusion Maps from PET-CT Images of Lung Cancer
The analysis of multi-modality positron emission tomography and computed...
10/05/2018 ∙ by Ashnil Kumar, et al. ∙
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Sparsity-based Convolutional Kernel Network for Unsupervised Medical Image Analysis
The availability of large-scale annotated image datasets coupled with re...
07/16/2018 ∙ by Euijoon Ahn, et al. ∙
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An unsupervised long short-term memory neural network for event detection in cell videos
We propose an automatic unsupervised cell event detection and classifica...
09/07/2017 ∙ by Ha Tran Hong Phan, et al. ∙
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Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)
Positron emission tomography (PET) image synthesis plays an important ro...
07/31/2017 ∙ by Lei Bi, et al. ∙
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Automatic Liver Lesion Detection using Cascaded Deep Residual Networks
Automatic segmentation of liver lesions is a fundamental requirement tow...
04/10/2017 ∙ by Lei Bi, et al. ∙
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High-Dimensional Data Visualization by Interactive Construction of Low-Dimensional Parallel Coordinate Plots
Parallel coordinate plots (PCPs) are among the most useful techniques fo...
09/17/2016 ∙ by Takayuki Itoh, et al. ∙
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