Attempt to Classi?cation and Localization of Thorax Diseases on ChestX-ray8 by Adaptive Structural Learning of Deep Belief Network
Bibliographic Information
- Other Title
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- ChestX-ray8を用いた構造適応型Deep Belief Networkにおける胸部疾患の分類と位置検出の試み
Description
Abstract?Deep Learning has a hierarchical network architecture to represent the complicated feature of in-put patterns. We have developed the adaptive structure learning method of Deep Belief Network (DBN) that can discover an optimal number of hidden neurons for given input data in a Restricted Boltzmann Machine (RBM) by neuron generation-annihilation algorithm, and hidden layers in DBN. We examined to the learning method to medical open database: CXR8. The CXR8 is one of the most commonly accessible radiological examination for screening and diagnosis of many lung diseases. This paper describes our method accuracy of the classi?cation and localization for the given bounding box(B-Box). The classi?cation ratio for 8 diseases were almost 100% score. A new localization method for DBN is proposed here and the discrete heatmap, the likelihood map of pathologies, was automatically constructed.
Journal
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- 2018 IEEE SMC Hiroshima Chapter若手研究会講演論文集
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2018 IEEE SMC Hiroshima Chapter若手研究会講演論文集 77-83, 2018
IEEE SMC Hiroshima Chapter
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Details 詳細情報について
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- CRID
- 1050859758014825856
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- NII Article ID
- 120006666398
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- Text Lang
- ja
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- Article Type
- conference paper
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- Data Source
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- IRDB
- CiNii Articles