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Infantile hemangiomas (IH) are a type of benign vascular tumors that appear within the first 5 months of life. The assessment of lesion size and its evolution in time is done manually by the physician, using a ruler, and this measurement is not very accurate. This paper presents a method for automatic measurement of the IH size. The work is divided in two parts: automatic computation of the size of...
We introduce a novel method of cell detection and segmentation based on a polar transformation. The method assumes that the seed point of each candidate is placed inside the nucleus. The polar representation, built around the seed, is segmented using k-means clustering into one candidate-nucleus cluster, one candidate-cytoplasm cluster and up to three miscellaneous clusters, representing background...
In this paper we introduce an automatic monitoring system for the detection and the evaluation of the evolution of hemangiomas using a fuzzy logic system based on two parameters: area and redness. We have considered pairs of images (from two different moments in time) that show hemangiomas either evolving, stationary or regressing. The starting points of the algorithm are the rectangular regions of...
In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing...
In this paper we propose a method for the automatic detection of hemangioma regions, consisting of a cascade of algorithms: a Self Organizing Map (SOM) for clustering the image pixels in 25 classes (using a 5x5 output layer) followed by a morphological method of reducing the number of classes (MMRNC) to only two classes: hemangioma and non-hemangioma. We named this method SOM-MMRNC. To evaluate the...
Infantile hemangiomas are the most common types of tumors with an incidence of approximately 10% in the common population. An accurate monitoring of the progress of hemangioma growth and regression is essential for an effective treatment. This study presents an automatic evaluation of the evolution of hemangioma on a follow-up series of images based on color and area features. A color constancy approach...
Infantile hemangiomas (IH) are benign vascular tumors, most of them appearing in the first weeks and developing until six months of age. The evaluation of the lesion size is usually made by the physician through manual measurement, which is inaccurate. This paper presents an algorithm for the automatic segmentation of the hemangioma region, relying on the Maximum a Posteriori (MAP) classification...
Zenker's diverticulum (ZD), also known as pharyngoesophageal diverticulum, is a relatively rare ailment in the pathology of the esophagus, which still accounts for 63% of the diverticula in this digestive segment, affecting men more frequently than women. This study comprises of 35 cases of patients (over the 2001–2014 period) at the Clinic of General and Esophageal Surgery, under the supervision...
A novel method for the detection and segmentation of nuclei and cells in Pap smear images is introduced. The method is based on a geometric analysis of iso- and edge-contours. For nuclei detection we employ isocontours taken at different levels of intensity and we report best detection (object) recall values as well as best segmentation precision values. For cell outline detection, we employ traditional...
The Babes-Papanicolaou test (also known as Pap smear) is a method of cervical cancer screening used to detect abnormal cells which are or can become cancerous. Since the visual inspection of pap smears is very time consuming, the need for automatic methods is required. This paper presents an algorithm for the automatic detection of nuclei within pap smears images. The algorithm relies in the highly...
Infantile hemangiomas are the most common types of tumors that are found in infants and have an incidence of approximately 10% in the common population. Although most infantile hemangiomas are self-involuting, due to their fast proliferation they may threaten vital anatomical structures and physiological functions; also, the involution process may take up to several years. An accurate monitoring of...
Dermoscopy is the primary tool used for pigmented skin lesion diagnosis. Despite the use of this relative new clinical method dermoscopy based, diagnose is still subjective and the diagnosis detection accuracy is about 75–80%. In this paper we present several enhancement pre-processing techniques applied on dermatoscopic images, such as black frame removal and hair removal in an automatically manner...
The use of digital image processing as a medical diagnosis aid is now well established, being slowly but successfully integrated directly within the medical imaging devices. The traditional use of digital image processing as a post-imaging technique is still interesting, especially for new approaches to classical applications or for pioneering new ones. Our studies in the field of near automatic interpretation...
Reaction-diffusion cellular neural networks have been studied because of their properties regarding processing time and capability of integration. The possibility of using them in image preprocessing and/or processing and the advantages and disadvantages of doing that are analyzed. The main objective is to find suitable sets of parameters (genes) that can enhance some useful properties of a dermatoscopic...
In this paper we present a triangular mesh simplification algorithm which produces accurate approximations of the original models. The simplification is realized using iterative edge contractions. The accuracy is obtained using a symmetric error metric and generating sample points over the simplified mesh. The sample points are generated using iterative 1 : 4 subdivisions of each triangle. The number...
Dermoscopy has become the primary tool used for pigmented skin lesion diagnosis providing better quality and accurate images. Computer-Assisted Image Interpretation is a new direction that involves the automatical lesion detection, feature extraction and classification (benign or malignant). This paper refers to several prior pre-processing enhancement techniques and an automated segmentation method...
This paper presents a new contour extraction algorithm for time-of-flight (ToF) camera distance images. Experimental results and comparisons with the classical grey level contour extractors are presented. A mathematical model for contour validation is developed, and finally, an edge alignment method is proposed.
According to the World Health Organization, breast cancer is the most common cancer suffered by women in the world, which during the last two decades, has increased the women mortality in developing countries. Mammography is the best method used for the screening; the problem of detecting possible cancer areas is very complex due, on one hand, to the diversity in shape of the ill tissue and, on the...
Detection of pectoral muscle in mammograms is an important pre-processing segmentation step. The pectoral muscle is one of the few anatomical features that appears clearly and reliably in medio-lateral oblique view mammograms. This new method overcomes the limitation of the straight-line representation considered in our initial investigation using the Hough transform.
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