Iatrogenic superior mesenteric artery syndrome

We have carefully read the article "Superior mesenteric artery syndrome: an uncommon cause of intestinal obstruction" by José Barquín-Yagüez et al. and we would like to report one case with the same diagnosis but with another etiology.info:eu-repo/semantics/publishedVersio

A review of algorithms for medical image segmentation and their applications to the female pelvic cavity

This paper aims to make a review on the current segmentation algorithms used for medical images. Algorithms are classified according to their principal methodologies, namely the ones based on thresholds, the ones based on clustering techniques and the ones based on deformable models. The last type is focused on due to the intensive investigations into the deformable models that have been done in the last few decades. Typical algorithms of each type are discussed and the main ideas, application fields, advantages and disadvantages of each type are summarised. Experiments that apply these algorithms to segment the organs and tissues of the female pelvic cavity are presented to further illustrate their distinct characteristics. In the end, the main guidelines that should be considered for designing the segmentation algorithms of the pelvic cavity are proposed

Forma rara de tumor carcinóide - caso clínico

ABSTRACTThe authors report a clinical case of carcinoid tumor, located at the antero-superior mediastjnum and of probable origin in thymus, whose local agressivity and metastatic pattern are in accordance with the references found in the medical literature about the clinical behaviour of the thymic carcinoid. They have not identified endocrine paraneoplasia, particularly the carcinoid syndrome.REV PORT PNEUMOL 2001; VII (4-5): 343-34

Absent abdominal muscles, nephro-urologic abnormalities, and severe neurologic damage in an infant with 3 chromosomal duplications: A novel syndrome?

Absent abdominal muscles, cryptorchidism, and hydroureteronephrosis are known to occur in the prune belly syndrome (PBS). We present a male with absent abdominal muscles, severe neurologic damage, with global developmental delay, hydroureteronephrosis, and cryptorchidism. The patient also had arthrogryposis multiplex congenital, low set ears, short neck, micrognathia, bilateral total ptosis, and bilateral clubfeet. Genetic testing (CGH array) revealed 3 novel duplications of unknown clinical significance at 7q11.23, 9q22.32 (PTCH 1 gene), and 12q21.32 (CEP 290 gene).Conclusion: We feel that our patient represents a novel entity, henceforth not described in the literature

Computational algorithms for the segmentation of the human ear

The main goal of this project is to identify an efficient segmentation algorithm for each anatomic structure of the ear. Therefore, in this paper, it is presented and analyzed computational algorithms that have been used to segment structures in images, especially of the human ear in Computed Tomography (CT) images

Effective Features to Classify Skin Lesions in Dermoscopic images

Features such as shape and color are indispensable to determine whether a skin lesion is a melanoma or not. However, there are no fixed guidelines to define which features are effective and how to combine them for classification. This lack of definition impedes the development of the automatic analyses of dermoscopic images. In this work, a search for effective features was carried out using a support vector machine. Three image databases were used to verify the feasibility and sensitivity of the automatic classification used. The results showed which features had a major influence on the classification performance, and confirmed the need to use various types of features in this process

A novel approach to segment skin lesions in dermoscopic images based on a deformable model

Abstract:Dermoscopy is an imaging technique that has been widely used in the diagnosis of skin lesions. However, its accuracy largely depends on the dermatologist's experience; thus, computer-aided diagnosis techniques are required. In this paper, a novel approach based on a deformable model is proposed to handle the segmentation of skin lesions in dermoscopic images. The RGB color space is converted so that the color information contained in the images can be used effectively to differentiate normal skin and skin lesions; and the differences in the color channels are combined together to define the speed function and the stopping criterion of the deformable model. This novel approach is robust against the noise, and provides an effective and flexible segmentation. Two image databases were used to test the performance of the novel approach and the segmentation results obtained were satisfactory. Quantitative analysis on 250 dermoscopic images showed that the novel algorithm outperformed other state-of-the-art algorithms. Also, using comparative data, the reliability and the implementation issues of the approach are discussed in this paper

Current trends of segmentation algorithms for skin lesions

Skin cancer has become one of the most frequent forms of cancer nowadays; its high prevalence has attracted many studies towards the causes and treatments in the recent years. However, the current practice of detecting skin cancers is fairly subjective and may suffer from diagnostic errors. In order to solve this problem, an effective computer-aided diagnosis (CAD) system is urgently demanded. Such system can provide an objective source to help the dermatologist improve the diagnostic accuracy. Such an automated system aims to detect the skin lesions on the acquired images and then analyzes whether those lesions are benign or malignant. The usual computational procedure is composed of three steps: image segmentation, feature extraction, and classification. Among these steps, the segmentation has deterministic influences to the later quantitative analysis and classification; however, due to the complicated appearance of skin lesions in the images, correct segmentation of their boundaries is very challenging. Many algorithms have been proposed to fulfill this task, and some of them have achieved satisfactory performances. Nevertheless, the performance of the existing algorithms still needs further improvement to be accepted in clinical practice. This paper will review these algorithms and summarize their trends of the development; algorithms focused in this work contain both the ones for dermoscopic images and the ones for macroscopic images. Advantages and disadvantages of each algorithm will be discussed; and possible techniques that can be used for improvement will be proposed. Open image database will be used for testing and for the illustration and comparisons among the different algorithms