Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

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Deep learning aided decision support for pulmonary nodules diagnosing: a review.Highly accurate model for prediction of lung nodule malignancy with CT scans.A 3-dimensional (3D)-printed Template for High Throughput Zebrafish Embryo Arraying

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P2860

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

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2017 nî lūn-bûn

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Automatic Categorization and S ...... Convolutional Neural Network.

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Automatic Categorization and S ...... Convolutional Neural Network.

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Automatic Categorization and S ...... Convolutional Neural Network.

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Automatic Categorization and S ...... h Convolutional Neural Network

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Daiqiang Chen

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Jie-Zhi Cheng

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Jingjing Gao

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Mei Xie

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Qingfeng Wang

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Samuel G Finlayson

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Xiaoguang Tu

http://www.w3.org/2001/XMLSchema#string

Zheng Ma

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P2860

Guidelines for Management of Small Pulmonary Nodules Detected on CT Scans: A Statement from the Fleischner Society 1

The Measurement of Observer Agreement for Categorical Data

Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines.

Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit

International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

Probability of cancer in pulmonary nodules detected on first screening CT.

Computer-aided diagnosis of pulmonary nodules on CT scans: improvement of classification performance with nodule surface features.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.

Accuracy of clinicians and models for estimating the probability that a pulmonary nodule is malignant.

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s41598-017-08040-8

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scholarly article

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10.1038/S41598-017-08040-8

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English

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Yangming Ou

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2017-09-01T00:00:00Z

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28864824

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convolutional neural network

automation

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5581338

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Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

about

P2860

P2860

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

description

name

type

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prefLabel

P1433

P1476

P2093

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P356

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P932