Computer-aided lung nodule diagnosis using a simple classifier · 1. Introduction · 2. Materials and methods · 3. Results · 4. Discussion.
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Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography ...
Jul 27, 2018 · Lung nodules diagnosed as benign nodules, primary lung cancers, or metastatic lung cancers were selected, and the CT images, final diagnosis, ...
Missing: classifier. | Show results with:classifier.
Results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that ...
May 12, 2023 · A CAD algorithm for the identification of pulmonary nodules was created and used on a retrospective cohort of patients with x-rays performed in 2008.
Jun 28, 2019 · We present an in-depth review and analysis of salient methods for computer-aided detection of lung nodules. We evaluate the current methods ...
This CAD system is able to automatically classify, quantify, and calculate the growth rate of pulmonary nodules. These results suggest that Deep Learning ...
Missing: simple classifier.
Apr 6, 2015 · This work is concerned with classification-based lung nodule detection. However, lung nodule classification is a typical unbalanced dataset ...
Multiple investigators have shown that use of a CADe algorithm can assist the radiologist in significantly increasing the rate of nodule detection.
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An early prediction and classification of lung nodule diagnosis on CT ...
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May 31, 2023 · The study demonstrated that the developed classification model was able to accurately classify lung nodules with a high degree of accuracy. The ...