By applying CBIR method iteratively and using pathologically confirmed cases, we expand the set of diagnosed data available for CAD systems from 17 nodules to ...
Abstract. In lung cancer computer-aided diagnosis (CAD) systems, having an accurate and available ground truth is critical and time consuming.
Correlation between Biopsy Confirmed Cases and Radiologist's Annotations in the Detection of Lung Nodules by Expanding the Diagnostic Database Using Content ...
Sep 27, 2016 · This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules, observed in lung CT images.
Missing: Confirmed Annotations Expanding
a completed reference database of lung nodules on CT scans.
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The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.
In this paper the framework for content-based image retrieval (CBIR) system for solid pulmonary nodules from lung CT images has been described.
Nov 8, 2023 · Deep Convolutional neural network–based software improves Radiologist detection of malignant lung nodules on chest Radiographs. Radiology ...
There could be a significant improvement in the field of lung nodule detection at an early stage of lung cancer and also ensures that unnecessary biopsies ...
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Oct 12, 2021 · The proposed content-based image retrieval system for chest CT images with deep learning improved the diagnostic accuracy of interstitial lung disease.
Missing: Annotations | Show results with:Annotations
... Biopsy Confirmed Cases and Radiologist's Annotations in the Detection of Lung Nodules by Expanding the Diagnostic Database Using Content Based Image Retrieval.