USE OF TEXTURES FOR MONITORING THE TREATMENT OF LEG ULCERS

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1 USE OF TEXTURES FOR MONITORING THE TREATMENT OF LEG ULCERS Gilmar Caiado Fleury Medeiros a João Eduardo Borelli b Adilson Gonzaga c a, c University of São Paulo, São Carlos Engineering School, Electrical Engineering Department, Computer Vision Laboratory, , São Carlos, SP, Brazil. Telephone: (16) b Technological Institute of Aeronautics, Mechanical Engineering Department, CTA, , São José dos Campos - SP, Brazil. gcaiado@sel.eesc.sc.usp.br a, jborelli@mec.ita.br b, adilson@sel.eesc.sc.usp.br c

2 Abstract Leg ulcers are dermatologic lesions that attack individuals with vascular and arterial deficiencies as well as neurological disorder. The main types of ulcers are the arterial and veined, followed by decubitus, diabetics or mixed. Leg lesions are of difficult healing, being enough common to individuals the occurrence of open wounds during years and that end for giving up the treatment because they notice not an improvement of the state of the lesions. The treatment of this type of pathology is usually made with application of pulses of low intensity ultrasound [1][2], on the harmed surface, or with the use of techniques of laser application [2], among others more recent [1][3][4]. All types of ulcers present visual characteristics, with the formation of several tissues, like the granulation tissue and slough [5], alterations of form, depth, color and area, what justifies the use of Computer Vision for the monitoring the evolution of the wound with the applied treatment. The monitoring of the state of the lesions is usually made through visual inspection, with the aid of pictures or films, or through invasive measures, such as the use of rulers combined with acetate paper, or by area measurement [3]. Such techniques possess some deficiencies, like the imprecision of the measures, as well as the possibility of infections caused by the contact of objects in the harmed area [1][3]. Several computer systems for monitoring lesion images can be found, such as [5][6][7][8]. Such systems emphasize the wound analysis starting from the segmentation of harmed areas and the color measurement of the same ones, obtaining comparative values used for the analysis of the behavior of the pathology. This work proposes a non-invasive method using texture features from the analysis of the wound areas of images. Textures are useful for the mensuration and comparison of structures that follow a non-linear pattern [9], which is the case of the analyzed wounds. For the analysis of non-linear structures, measures are proposed through second order statistics, with the use of Haralick is features [10][11][12]. Five features were selected in order to be appraised: angular second moment, contrast, entropy, inverse differential moment and correlation. The angular second moment angular measures homogeneity,

3 the contrast measures the amount of gray levels local variations, the entropy measures the dispersion of the points and the inverse differential moment and the correlation measure the gray levels concentration in certain points of the area as well as the area linearity, respectively. Several works have been made in the medical area using textures and their respective statistical analysis, like the case of the analysis of patient having Alzheimer disease [13], through the use of nuclear magnetic resonance images and in mamographics images [14] [15], for the detection of microcalcification areas. A system composed by three modules was developed for that goal: acquisition, preprocessing and feature extraction. The acquisition module consists of a CCD camera coupled in a microcomputer, through a frame-grabber. The second module prepares the image for the features be extracted, converting it for gray levels and proceed to an operation of texture sampling of the internal area of the ulcer, followed by the histogram equalization of each sample, in order to enhance the different types of wound structures. The third module extracts the features of Haralick. Several images of two patients presenting case of cicatrization were classified in their dates and submitted afterwards to the software for the obtaining the features. The results are presented in graphics and tables exposed in a way to facilitate the health area professional for the attendance of the patient is state in several stages of the evolution of the pathology. Possessing those graphics turns also possible to do the comparison of the state of the lesion of two patients, evaluating the efficiency of the applied treatment under them. It is important for the patient to know that he is being recovered, what is of fundamental importance for continuity of the treatment and to increase his self-esteem. Key-words: image processing; textures; leg ulcers; computer systems for medical diagnostic.

4 References [1] HILÁRIO, M. (1993). Low Intensity Ultrasonic Radiation for Tissue Recover of Trophic Leg Ulcers - São Carlos, EESC, University of São Paulo, Master Thesis. [2] SUGRUE, M. E. et al. (1990). The Use of Infrared Laser Theraphy in the Treatment of Venous Ulceration. Ann. Vasc. Surg., vol.4, no.2, pp [3] SUSSMAN, C.; BATES-JENSEN, B. M. (1998). Wound Care - A Collaborative Practice Manual for Physical Therapists and Nurses. Aspen Publishers, Inc. [4] RUBIN J. R. et al. (1990). Unnas Boot versus Pollyuretane Foan Dressings for the Treatment of Venous Ulcerations: a Randomized Prospective Study. Archives of Surgery, vol. 125, no.4, pp [5] BERRIS, W. P. (2000). Acquisition of Skin Wound Images and Measurement of Wound Healing Rate and Status Using Colour Image Processing. University of Reading, Department of Engineering, Ph.D Thesis, September. [6] HERBIN, M.; BON, F. X. et al. (1993). Assessment of Healing Kinetics Throught True Color Image Processing. IEEE Transactions on Medical Imaging, vol. 12, no. 1, pp [7] HERBIN, M.; VENOT, A. et al. (1990). Color Quantitation Through Image Processing in Dermatology. IEEE Transactions on Medical Imaging, vol. 9, no. 3, pp [8] VENOT, A.; DEVAUX, J. Y. et al. (1988). An automated system for registration and comparison of photographic images in medicine. IEEE Transactions on Medical Imaging, vol. TMI-7, no. 4, pp

5 [9] PRATT, W. K. (1991). Digital Image Processing. Wiley Interscience, Second Edition. [10] HARALICK, R. M. et al. (1973). Textural Features for Image Classification. IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-3, n. 6, November. [11] HARALICK, R. M.; SHANMUGAM, K (1973). Computer Classification of Reservoir Sandstones. IEEE Transactions on Geoscience Electronics, vol. GE-11, pp , October. [12] AKSOY, S; HARALICK, R. M. (1999). Using Texture in Image Similarity and Retrieval. Intl. Workshop on Texture Analysis in Machine Vision, pp , Finland, June. [13] BURRILL, J. H. P. (1999). Texture Mapping of Neurological Magnetic Resonance Images, 3 rd Year Individual Project, Imperial College of Science, Technology & Medicine, Department of Electrical and Electronic Engineering, last visited in 10/01/2001. [14] GUPTA, R.; UNDRILL P. E. (1996). The Use of Texture Analysis to Identify Suspicious Masses in Mammography. University of Aberdeen, Foresterhill, Scotland. Department of Bio-Medical Physics & BioEngineering, last visited in 10/01/2001. [15] MEERSMAN, D. et al. (1998). Classification of Micro Calcifications using Texture-Based Features. 4 th International Workshop on Digital Mammography, June 7-10, University of Nijmegen, The Netherlands.

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