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To improve the accuracy and sensitivity of the breast tumor classification based on ultrasound images, a computer-aided classification algorithm is proposed using the Affinity Propagation (AP) clustering. Five morphologic features and three texture features are extracted from each breast ultrasound image. The AP clustering with an empirical value of "preference" is used as the primary classification...
Feature extracted from structural irregularity for skin lesion boundaries has a great significance in computer-aided diagnosis for melanomas. Based on previous work using local fractal dimension (local FD) for contour irregularity descriptions, the novelty of this paper focuses on: (1) Multi-scaled curvature analysis is used to acquire features of boundary irregularity (2) Feature differences from...
Boundary roughness of skin lesions is of clinical significance for early detection of malignant melanomas. An integrated approach of local fractals and multi-level wavelet analysis is proposed in the paper. Local fractal profile of a lesion contour is generated to describe boundary roughness while a tree structured wavelet packet is further processed to give behaviors of the local fractals at different...
Objective The aim of this study was to explore the clinical value of the combination of prior knowledge of physicians and texture features for differentiation of malignant from benign solitary pulmonary nodules(SPNs) and mass lesions based on 18F-FDG PET/CT. Methods 143 patients with known solitary pulmonary nodule or mass were enrolled in the study. All the patients underwent 18F-FDG PET/CT examination...
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