False-Positive Reduction on Lung Nodules Detection in Chest Radiographs by Ensemble of Convolutional Neural Networks
نویسندگان
چکیده
منابع مشابه
False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network.
RATIONALE AND OBJECTIVE We developed a technique that uses a multiple massive-training artificial neural network (multi-MTANN) to reduce the number of false-positive results in a computer-aided diagnostic (CAD) scheme for detecting nodules in chest radiographs. MATERIALS AND METHODS Our database consisted of 91 solitary pulmonary nodules, including 64 malignant nodules and 27 benign nodules, ...
متن کاملComputer-Aided Detection of Malignant Lung Nodules on Chest Radiographs: Effect on Observers' Performance
OBJECTIVE To evaluate the effect of computer-aided detection (CAD) system on observer performance in the detection of malignant lung nodules on chest radiograph. MATERIALS AND METHODS Two hundred chest radiographs (100 normal and 100 abnormal with malignant solitary lung nodules) were evaluated. With CT and histological confirmation serving as a reference, the mean nodule size was 15.4 mm (ra...
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OBJECTIVE The aim of this study was to evaluate the usefulness of a new commercially available computer-aided diagnosis (CAD) system with an automated method of detecting nodules due to lung cancers on chest radiograph. MATERIALS AND METHODS For patients with cancer, 45 cases with solitary lung nodules up to 25 mm in diameter (nodule size range, 8-25 mm in diameter; mean, 18 mm; median, 20 mm...
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A new computer aided detection (CAD) system is presented for the detection of pulmonary nodules on chest radiographs. Here, we present the details of the proposed algorithm and provide a performance analysis using a publicly available database to serve as a benchmark for future research efforts. All aspects of algorithm training were done using an independent dataset containing 167 chest radiog...
متن کاملComputer-aided detection (CAD) of lung nodules and small tumours on chest radiographs.
Detection of focal pulmonary lesions is limited by quantum and anatomic noise and highly influenced by variable perception capacity of the reader. Multiple studies have proven that lesions - missed at time of primary interpretation - were visible on the chest radiographs in retrospect. Computer-aided diagnosis (CAD) schemes do not alter the anatomic noise but aim at decreasing the intrinsic lim...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2817023