A Multi-Classifier System for Pulmonary Nodule Classification

2008 ◽  
Author(s):  
Michela Antonelli ◽  
Marco Cococcioni ◽  
Beatrice Lazzerini ◽  
Francesco Marcelloni ◽  
Dan Stefanescu
Keyword(s):  
Pulmonary Nodule ◽  
Classifier System ◽  
Nodule Classification

scholarly journals Pulmonary Nodule Classification Using Feature and Ensemble Learning Based Fusion Techniques

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Muhammad Muzammil ◽  
Imdad Ali ◽  
Ihsan Ul Haq ◽  
Amir A. Khaliq ◽  
Suheel Abdullah
Keyword(s):  
Ensemble Learning ◽  
Pulmonary Nodule ◽  
Nodule Classification

Image-guided decision support system for pulmonary nodule classification in 3D thoracic CT images

2004 ◽  
Author(s):  
Yoshiki Kawata ◽  
Noboru Niki ◽  
Hironobu Ohmatsu ◽  
Masahiro Kusumoto ◽  
Ryutaro Kakinuma ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Pulmonary Nodule ◽  
Ct Images ◽  
Image Guided ◽  
Thoracic Ct ◽  
Nodule Classification

Pulmonary nodule classification with deep residual networks

2017 ◽  
Vol 12 (10) ◽  
pp. 1799-1808 ◽  
Author(s):  
Aiden Nibali ◽  
Zhen He ◽  
Dennis Wollersheim
Keyword(s):  
Pulmonary Nodule ◽  
Nodule Classification

scholarly journals CNN Hyperparameter Optimization for Pulmonary Nodule Classification

2020 ◽  
Author(s):  
Anthony Jatobá ◽  
Lucas Lima ◽  
Lucas Amorim ◽  
Marcelo Oliveira
Keyword(s):  
Pulmonary Nodule ◽  
Hyperparameter Optimization ◽  
Nodule Classification

Redes Neurais Convolucionais (RNCs) são uma técnica poderosa para sistemas de diagnóstico auxiliado por computador, mas a configuração manual de redes complexas é inviável. A otimização automática de hiper-parâmetros é uma abordagem promissora, mas não há consenso sobre a técnica mais adequada. Neste trabalho, comparamos busca direta, probabilística e otimização bayesiana na otimização de RNCs 2D e 3D para classificação de nódulos pulmonares. Foram obtidas AUC de 0,88, sensibilidade de 87,03% e especificidade de 78,66%. Nossos experimentos demonstram o fraco desempenho da busca em grade, enquanto mostram que técnicas simples, como a busca aleatória, pode ter desempenho comparável a abordagens probabilísticas

Pulmonary nodule classification based on CT density distribution using 3D thoracic CT images

2004 ◽  
Author(s):  
Yoshiki Kawata ◽  
Noboru Niki ◽  
Hironobu Ohamatsu ◽  
Masahiko Kusumoto ◽  
Ryutaro Kakinuma ◽  
...  
Keyword(s):  
Density Distribution ◽  
Pulmonary Nodule ◽  
Ct Images ◽  
Thoracic Ct ◽  
Ct Density ◽  
Nodule Classification

Investigation of pulmonary nodule classification using multi-scale residual network enhanced with 3DGAN-synthesized volumes

2020 ◽  
Vol 13 (2) ◽  
pp. 160-169 ◽  
Author(s):  
Yuya Onishi ◽  
Atsushi Teramoto ◽  
Masakazu Tsujimoto ◽  
Tetsuya Tsukamoto ◽  
Kuniaki Saito ◽  
...  
Keyword(s):  
Pulmonary Nodule ◽  
Residual Network ◽  
Multi Scale ◽  
Nodule Classification
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