Implementation of an infrared imaging system for vascular detection in the forearm and hand

Abstract

The venipuncture, the catheterization and intravenous (IV) injections are some of the common procedures in the clinical practice. The location of the veins may be complex in some patients. In this paper a system able to enhance the vein distribution in a patient’s forearm in order to help, in future works, to locate the veins in a non-invasive way and accomplish the IV procedures, is described. To carry out this work a web cam was used, the filter that blocks out the infrared light has been removed and replaced for one who does not. To increase the vein detection an array of infrared LEDs (830 nm) was attached. The resulting images were processed using the adaptive histogram equalization and then classified by two methods, the first one based on the Fuzzy C-Means Algorithm, and the secondbased in a Bayesian probabilistic model. For the image acquisition, the anterior-exterior regions of the left and right forearm of each subject were considered to generate a data base. This system also has relevance in the detection ofvaricose veins since is able to monitor the vein dilatation.

A fuzzy approach for feature extraction of brain tissues in Non-Contrast CT

“…Berndt et al [11] evalu- has the potential to combine human heuristics in computer-aided decision making, it opens the door to construction of better models of reality and involves exploitation of a tolerance for imprecision [12] . Fuzzy logic has been applied in all disciplines of medicine in some form of classification, detection, segmentation and control [13][14] [15] , and recently its applicability in neurosciences, especially in brain tissue segmentation, is also increasing [16][17] [18] .…”