Robust Feature for Transcranial Sonography Image Classification Using Rotation-Invariant Gabor Filter
نویسندگان
چکیده
Experiment 2: TCS images were obtained by Philips SONOS 5500 with different examiners. Totally, 67 images from 38 PD patients and 71 images from 39 healthy subjects were included. All 77 subjects underwent a neurological examination. The rotationinvariant Gabor filter bank was applied to the ROI of TCS images. Then the Gabor features, mean, std and entropy, were calculated and evaluated by SVMs with linear kernel. At last, the sequential forward floating selection (SFFS) method was implemented to select the feature subset which achieved the best classification rate.
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