No abstract

No abstract

Abstract. This work presents a new method for automatic threshold selection and its application for bone segmentation in CT images. Based on the mean (μ) and standard deviation (σ) values of an automatically selected region from a Gabor filter response, the proposed method prevents the misclassification of medium and high-valued pixels in images with high density of low-valued (background) pixels like those in medical images. The method obtains an average accuracy of 98.9% and a mean local accuracy of 76.7% using a database of 60 CT images. In addition, the proposed method shows a better performance than the comparative threshold (Otsu and Kittler) and clustering (Fuzzy C-means and K-means) methods applied under same conditions.

No abstract

All around the world, partial or total blindness has become a direct consequence of diabetes and hypertension. Visual disorders related to these diseases require automatic and specialized methods to detect early malformations, artifacts, or irregular structures for helping specialists in the diagnosis. This study presents an innovative methodology for detecting and evaluating retinopathies, particularly microaneurysm and hemorrhages. The method is based on a multidirectional Fractional-Order Gaussian Filters tuned by the Differential Evolution algorithm. The contrast of the microaneurysms and hemorrhages, regarding the background, is improved substantially. After that, these structures are extracted using the Kittler thresholding method under additional considerations. Then, candidate lesions are detected by removing the blood vessels and fovea pixels in the resulting image. Finally, candidate lesions are classified according to its size, shape, and intensity properties via Support Vector Machines with a radial basis function kernel. The proposed method is evaluated by using the publicly available database MESSIDOR for detecting microaneurysms. The numerical results are summarized by the averaged binary metrics of accuracy, sensitivity, and specificity giving the performance values of 0.9995, 0.7820 and 0.9998, respectively.

No abstract