Ontology of gaps in content-based image retrieval
TM Deserno, S Antani, R Long - Journal of digital imaging, 2009 - Springer
Content-based image retrieval (CBIR) is a promising technology to enrich the core
functionality of picture archiving and communication systems (PACS). CBIR has a potential …
functionality of picture archiving and communication systems (PACS). CBIR has a potential …
Predicting radiological panel opinions using a panel of machine learning classifiers
This paper uses an ensemble of classifiers and active learning strategies to predict
radiologists' assessment of the nodules of the Lung Image Database Consortium (LIDC). In …
radiologists' assessment of the nodules of the Lung Image Database Consortium (LIDC). In …
Differential geometry-based techniques for characterization of boundary roughness of pulmonary nodules in CT images
Purpose Boundary roughness of a pulmonary nodule is an important indication of its
malignancy. The irregularity of the shape of a nodule is represented in terms of a few …
malignancy. The irregularity of the shape of a nodule is represented in terms of a few …
Toward understanding the size dependence of shape features for predicting spiculation in lung nodules for computer-aided diagnosis
R Niehaus, D Stan Raicu, J Furst, S Armato - Journal of digital imaging, 2015 - Springer
We analyze the importance of shape features for predicting spiculation ratings assigned by
radiologists to lung nodules in computed tomography (CT) scans. Using the Lung Image …
radiologists to lung nodules in computed tomography (CT) scans. Using the Lung Image …
Semantic characteristics prediction of pulmonary nodule using artificial neural networks
G Li, H Kim, JK Tan, S Ishikawa… - 2013 35th Annual …, 2013 - ieeexplore.ieee.org
Since it is difficult to choose which computer calculated features are effective to predict the
malignancy of pulmonary nodules, in this study, we add a semantic-level of Artificial Neural …
malignancy of pulmonary nodules, in this study, we add a semantic-level of Artificial Neural …
Modelling semantics from image data: opportunities from LIDC
While the advances in Computed Tomography (CT) technology allow better detection of
pulmonary nodules by generating higher-resolution images, the new technology also …
pulmonary nodules by generating higher-resolution images, the new technology also …
A novel approach to nodule feature optimization on thin section thoracic CT
RATIONALE AND OBJECTIVES: An analysis for the optimum selection of image features in
feature domain to represent lung nodules was performed, with implementation into a …
feature domain to represent lung nodules was performed, with implementation into a …
Agreement of CAD features with expert observer ratings for characterization of pulmonary nodules in CT using the LIDC-IDRI database
R Wiemker, M Bergtholdt, E Dharaiya… - Medical Imaging …, 2009 - spiedigitallibrary.org
We have analyzed 3000 nodule delineations and malignancy ratings of pulmonary nodules
made by expert observers in the IDRI CT lung image database. The agreement between …
made by expert observers in the IDRI CT lung image database. The agreement between …
Isolated pulmonary nodules characteristics detection based on CT images
Pulmonary nodules are the main pathological changes of the lung. Malignant pulmonary
nodules will be transformed into lung cancer, which is a serious threat to human health and …
nodules will be transformed into lung cancer, which is a serious threat to human health and …
[HTML][HTML] Detection of juxtapleural nodules in lung cancer cases using an optimal critical point selection algorithm
S Saraswathi, LMI Sheela - Asian Pacific journal of cancer …, 2017 - ncbi.nlm.nih.gov
Detection of lung cancer through image processing is an important tool for diagnosis. In
recent years, image processing techniques have become more widely used. Lung …
recent years, image processing techniques have become more widely used. Lung …