ABSTRACT
OBJECTIVE@#In order to obtain more decision information from Digital Radiography(DR) images, an improved image enhancement algorithm is proposed based on the algorithm of Gauss-Laplacian pyramid.@*METHODS@#The original algorithm is improved on the basis of the human visual characteristics and better enhancements, the low frequency components of the image is histogram equalized to make the image gray scale more balanced, and the high frequency component is enhanced by a hierarchical exponential enhancement to make the details of the image clearer.@*RESULTS@#The improved algorithm improves the contrast of DR images in chest, pelvic and spine, and makes the image more layered and obtains good image enhancement effect.@*CONCLUSIONS@#The results show that the improved algorithm is superior to the traditional algorithm in terms of image enhancement.
Subject(s)
Humans , Algorithms , Image Enhancement , Radiographic Image EnhancementABSTRACT
RESUMEN: En el área clínica son procedimientos comunes la venopunción, la colocación de catéteres, inyecciones intravenosas, etc. La visualización de las venas en algunas personas es compleja. En este trabajo se presenta el desarrollo de un sistema capaz de realzar la distribución de las venas en el antebrazo de una persona para, en un trabajo futuro, ayudar de forma no invasiva a localizar las venas en los procedimientos de venopunción. Para llevar a cabo el desempeño de esta tarea se utilizó una cámara web, a la cual se le ha extraído el filtro que impide el paso de luz infrarroja y es sustituido por otro que lo permite. Para mejorar la detección de las venas se le agregó a la cámara un arreglo de LEDs emisores de luz infrarroja (830nm). Las imágenes obtenidas fueron procesadas mediante la ecualización del histograma adaptable y clasificadas por dos métodos, el primero basado en el algoritmo Fuzzy C-Means, el segundo basado en un modelo probabilístico de tipo Bayes, técnicas del área de inteligencia artificial, presentadas como alternativa en el procesamiento de imágenes. Para la obtención de las imágenes se consideraron las regiones anteriores y exteriores del antebrazo izquierdo y derecho de cada sujeto generando una base de datos. Este sistema también tiene aplicación en la detección de venas varicosas debido a que se puede dar un seguimiento a la dilatación de las venas.
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 second based 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 of varicose veins since is able to monitor the vein dilatation.
ABSTRACT
Objective:A more effective approach to judge the fissure fracture by using image enhancement is presented.Methods:The Gradient image after 5×5 median filtering smoothing was used to mask the laplace image, and to add the original image in order to informing the sharpening image, and then the adaptive contrast histogram equalization is put in shaping image and to compare the effect of the image enhancement.Results: The algorithm to enhance the X-Ray fracture image can highlight the shape of the fissure fracture clearly. The enhanced image is more effective than the image by using one way alone.Conclusion: This method is valuable in judging the fissure fracture in clinical diagnosis.
ABSTRACT
The general theories of gray correction methods for the medical ultrasonic image are introduced in this paper, including gray level correction, gray level transformation and histogram correction. The dominant histogram equalization method is expatiated and modified against its disadvantages including inapparent enhancement of partial detail and non-interactivity. Series connections of several gray correction methods are used to treat with the ultrasonic image, and thus its utility is improved through the selective enhancement of the contrast of certain gray scope.
ABSTRACT
Objective To select the proper enhanced methods of histogram egualization for the medical digital image. Methods By means of the full-frame histogram equalization(FFHE),local-area histogram equalization(LAHE) and adaptive-meighborhood histogram equalization(ANHE),medical digital images were enhanced,and the characteristics of these three methods were compared. Results Through the gray-level histogram equalization,the detail and the edge of medical digital images could be enhanced. Conclusion Toenhance the detail of local issue,it is better to use ANHE method.To enhance the edge of full image,which the full information must been taken into account,it is better to use FFHE method.