Computer-Aided Diagnosis for Pnemoconiosis Using Neural Network
CBMS '01 Proceedings of the Fourteenth IEEE Symposium on Computer-Based Medical Systems
CBMS '01 Proceedings of the Fourteenth IEEE Symposium on Computer-Based Medical Systems
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
New Image Processing Models for Opacity Image Analysis in Chest Radiographs
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
Am-fm image models
Analyzing Image Structure by Multidimensional Frequency Modulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale AM-FM analysis of pneumoconiosis X-ray images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy
IEEE Transactions on Image Processing
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We propose the use of Amplitude-Modulation Frequency-Modulation (AM-FM) features for representing and retrieving X-Ray images with pneumoconiosis. The AM-FM features are estimated using multiscale filterbanks with wavelengths related with the standard sizes for grading the level of opacities in X-Rays. The extracted AM-FM features represent opacity profusion in terms of instantaneous frequency (IF) and instantaneous amplitude (IA) features. Here, IF estimates in the medium and high scale frequencies can be used to capture early disease symptoms. AM-FM features from the low and medium scale frequencies are associated with advanced disease stages. We demonstrate the performance of the system in X-ray image retrieval and classification applications.