Classification of Idiopathic Interstitial Pneumonia CT Images using Convolutional-net with Sparse Feature Extractors

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概要

• 論文の詳細を見る

• We propose a computer aided diagnosis (CAD) system for classification of idiopathic interstitial pneumonias (IIPs). High resolution computed tomography (HRCT) images are considered as effective for diagnosis of IIPs. Our proposed CAD system is based on the convolutional-net that is bio-plausible neural network model inspired from the visual system such like human. The convolutional-net extract local features and integrate them in the process of hierarchical neural network system. For natural image recognition by convolutionalnet, Gabor feature extraction is known to give a good performance, however, the HRCT images may have different properties from those of natural images. Thus, we introduce a learning type feature extraction called "sparse coding" into the convolutional-net, and evaluate performance for classification of IIPs.

• 2011-07-11

著者

• Hayaru Shouno

  Graduate School of Informatics and Engineering, University of Electro-Communications

• Shoji Kido

  Applied Medical Engineering Sciece Graduate School Of Medicine Yamaguchi University

• Kido Shoji

  Yamaguchi University

• Hayaru Shouno

  Graduate School Of Informatics And Engineering University Of Electro-communications

• Kido Shoji

  Applied Medical Engineering Science Graduate School Of Medicine Yamaguchi University

• Taiju Inagaki

  Graduate School of Informatics and Engineering, University of Electro-Communications

• Shoji Kido

  Graduate School of Medicine, Yamaguchi Univeristy

• Shoji Kido

  Graduate School Of Medicine Yamaguchi Univeristy

• Taiju Inagaki

  Graduate School Of Informatics And Engineering University Of Electro-communications

関連論文

• Classification of Idiopathic Interstitial Pneumonia on High-resolution CT Images using Counter-propagation Network
• Classification of Idiopathic Interstitial Pneumonia CT Images using Convolutional-net with Sparse Feature Extractors
• Analysis of idiopathic interstitial pneumonia by self organization map on high-resolution computed tomography images (数理モデル化と問題解決)
• 3D Non-rigid Image Registration Assisted for Pneumoperitoneum in Laparoscopic Surgery
• Discrimination of Lung Sounds using a Statistics of Waveform Intervals
• A hierarchical extension of the HOG model implemented in the convolution-net for human detection
• Poisson Observed Image Restoration using a Latent Variational Approximation with Gaussian MRF
• Classification of Pneumoconiosis on HRCT Images for Computer-Aided Diagnosis
• A Computer-aided Diagnosis Method for Classification of Pneumoconiosis Patterns on HRCT Images

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