Uma metodologia híbrida para segmentação de lesões de pele

Computer aided methods are widespread demanded in medical applications. As such, methodologies to automatic extract contours are desired to aid the automatic diagnosis of skin lesions. In this work, we propose a hybrid method to detect and extract skin lesion contours from dermatoscopic images. In the proposed method, to obtain the contour that includes all lesion regions, the region growing technique, based on a Quadtree implementation, is used to extract an initial contour. Afterwards, this contour is refined by using a traditional active contour model. Experimental results indicate that the proposed method is promising to detect skin lesion areas and to extract their contours from dermatoscopic images. Actually, the extracted contours maintain the original lesion features that are usually used in their diagnosis. Additionally, the results allow concluding that the method is able to detect lesion regions even in images with strong noise, like in images of the scalp

Simultaneous image color correction and enhancement using particle swarm optimization

Color images captured under various environments are often not ready to deliver the desired quality due to adverse effects caused by uncontrollable illumination settings. In particular, when the illuminate color is not known a priori, the colors of the objects may not be faithfully reproduced and thus impose difficulties in subsequent image processing operations. Color correction thus becomes a very important pre-processing procedure where the goal is to produce an image as if it is captured under uniform chromatic illumination. On the other hand, conventional color correction algorithms using linear gain adjustments focus only on color manipulations and may not convey the maximum information contained in the image. This challenge can be posed as a multi-objective optimization problem that simultaneously corrects the undesirable effect of illumination color cast while recovering the information conveyed from the scene. A variation of the particle swarm optimization algorithm is further developed in the multi-objective optimization perspective that results in a solution achieving a desirable color balance and an adequate delivery of information. Experiments are conducted using a collection of color images of natural objects that were captured under different lighting conditions. Results have shown that the proposed method is capable of delivering images with higher quality. © 2013 Elsevier Ltd. All rights reserved

Uma metodologia híbrida para segmentação de lesões de pele

Computer aided methods are widespread demanded in medical applications. As such, methodologies to automatic extract contours are desired to aid the automatic diagnosis of skin lesions. In this work, we propose a hybrid method to detect and extract skin lesion contours from dermatoscopic images. In the proposed method, to obtain the contour that includes all lesion regions, the region growing technique, based on a Quadtree implementation, is used to extract an initial contour. Afterwards, this contour is refined by using a traditional active contour model. Experimental results indicate that the proposed method is promising to detect skin lesion areas and to extract their contours from dermatoscopic images. Actually, the extracted contours maintain the original lesion features that are usually used in their diagnosis. Additionally, the results allow concluding that the method is able to detect lesion regions even in images with strong noise, like in images of the scalp