Computer-Aided Diagnosis of Lung Nodules on CT Scans:
نویسندگان
چکیده
منابع مشابه
A Computer-Aided Diagnosis for Evaluating Lung Nodules on Chest CT: the Current Status and Perspective
As the detection and characterization of lung nodules are of paramount importance in thoracic radiology, various tools for making a computer-aided diagnosis (CAD) have been developed to improve the diagnostic performance of radiologists in clinical practice. Numerous studies over the years have shown that the CAD system can effectively help readers identify more nodules. Moreover, nodule malign...
متن کاملPulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection.
PURPOSE To compare the performance of radiologists and of a computer-aided detection (CAD) algorithm for pulmonary nodule detection on thin-section thoracic computed tomographic (CT) scans. MATERIALS AND METHODS The study was approved by the institutional review board. The requirement of informed consent was waived. Twenty outpatients (age range, 15-91 years; mean, 64 years) were examined wit...
متن کاملComputer Aided Diagnosis For the Detection of Lung Nodules
Lungs segmentation is a vital step for computer aided diagnosis. Many lungs diseases requiring radiological support for diagnostic purpose, including tuberculosis, emphysema and lungs cancer could be affectively diagnosed using computer-aid. Pulmonary nodules usually act as the early stage characterization of lung cancer. It’s a crucial way to control the disease and reduce the mortality by fur...
متن کاملComputer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans
This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx ...
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ژورنال
عنوان ژورنال: Academic Radiology
سال: 2010
ISSN: 1076-6332
DOI: 10.1016/j.acra.2009.10.016