Collateral motion saliency-based model for Trypanosoma cruzi detection in dye-free blood microscopy.

The motion performed by some protozoa is a crucial visual stimulus in microscopy analysis, especially when they have almost imperceptible morphological characteristics. Microorganisms can be distinguished through the interactions of their locomotion with neighboring elements, as observed in some parasitological analysis of Trypanosoma cruzi. In dye-free blood microscopy, the low contrast of this parasite makes it difficult to detect them. Thus, the parasite's interaction with the neighborhood, such as collisions with blood cells and shocks during the escape of confinements in cell clumps, generates collateral motions that assist its detection. Assuming that the collateral motion of the parasite can be sufficiently noticeable to overcome the dynamic contexts of inspection, we propose a novel computational approach that is based on motion saliency. We estimate motion in microscopy videos using dense optical flow and we investigate vestiges in saliency maps that could characterize the collateral motion of parasites. Our biological-inspired method shows that the parasite's collateral motion is a relevant feature for T. cruzi detection. Therefore, our computational model is a promising aid in the research and medical diagnosis of Chagas disease.

Saliency-driven system models for cell analysis with deep learning.

BACKGROUND AND OBJECTIVES: Saliency refers to the visual perception quality that makes objects in a scene to stand out from others and attract attention. While computational saliency models can simulate the expert's visual attention, there is little evidence about how these models perform when used to predict the cytopathologist's eye fixations. Saliency models may be the key to instrumenting fast object detection on large Pap smear slides under real noisy conditions, artifacts, and cell occlusions. This paper describes how our computational schemes retrieve regions of interest (ROI) of clinical relevance using visual attention models. We also compare the performance of different computed saliency models as part of cell screening tasks, aiming to design a computer-aided diagnosis systems that supports cytopathologists. METHOD: We record eye fixation maps from cytopathologists at work, and compare with 13 different saliency prediction algorithms, including deep learning. We develop cell-specific convolutional neural networks (CNN) to investigate the impact of bottom-up and top-down factors on saliency prediction from real routine exams. By combining the eye tracking data from pathologists with computed saliency models, we assess algorithms reliability in identifying clinically relevant cells. RESULTS: The proposed cell-specific CNN model outperforms all other saliency prediction methods, particularly regarding the number of false positives. Our algorithm also detects the most clinically relevant cells, which are among the three top salient regions, with accuracy above 98% for all diseases, except carcinoma (87%). Bottom-up methods performed satisfactorily, with saliency maps that enabled ROI detection above 75% for carcinoma and 86% for other pathologies. CONCLUSIONS: ROIs extraction using our saliency prediction methods enabled ranking the most relevant clinical areas within the image, a viable data reduction strategy to guide automatic analyses of Pap smear slides. Top-down factors for saliency prediction on cell images increases the accuracy of the estimated maps while bottom-up algorithms proved to be useful for predicting the cytopathologist's eye fixations depending on parameters, such as the number of false positive and negative. Our contributions are: comparison among 13 state-of-the-art saliency models to cytopathologists' visual attention and deliver a method that the associate the most conspicuous regions to clinically relevant cells.

Lung disease detection using feature extraction and extreme learning machine

INTRODUCTION: The World Health Organization estimates that by 2030 the Chronic Obstructive Pulmonary Disease (COPD) will be the third leading cause of death worldwide. Computerized Tomography (CT) images of lungs comprise a number of structures that are relevant for pulmonary disease diagnosis and analysis. METHODS: In this paper, we employ the Adaptive Crisp Active Contour Models (ACACM) for lung structure segmentation. And we propose a novel method for lung disease detection based on feature extraction of ACACM segmented images within the cooccurrence statistics framework. The spatial interdependence matrix (SIM) synthesizes the structural information of lung image structures in terms of three attributes. Finally, we perform a classification experiment on this set of attributes to discriminate two types of lung diseases and health lungs. We evaluate the discrimination ability of the proposed lung image descriptors using an extreme learning machine neural network (ELMNN) comprising 4-10 neurons in the hidden layer and 3 neurons in the output layer to map each pulmonary condition. This network was trained and validated by applying a holdout procedure. RESULTS: The experimental results achieved 96% accuracy demonstrating the effectiveness of the proposed method on identifying normal lungs and diseases as COPD and fibrosis. CONCLUSION: Our results lead to conclude that the method is suitable to integrate clinical decision support systems for pulmonary screening and diagnosis.

Tratamento cirúrgico da endocardite infecciosa näo-protética / Surgical treatment of non-prosthetic infective endocarditis

Quinze pacientes com endocardite infecciosa foram revistos a partir da experiência dos autores nos dois últimos anos. A idade variou de 16 a 44 anos, näo havendo nítida prevalência quanto ao sexo ou à raça. A maior parte das hemoculturas era negativa. Os pacientes tinham prognóstico reservado, apresentando pelo menos duas ou três das indicaçöes cirúrgicas maiores estabelecidas na literatura. Apesar de o risco operatório ser alto, a mortalidade pré-operatória foi de 0% e a pós-operatória de 20%. Em vista destes resultados e da alta morbidade com o tratamento clínico isolado, recomendam uma conduta agressiva com a intervençäo cirúrgica precoce, o que seguramente melhora em muito a sobrevida desses enfermos. Enfatizam que o ecocardiograma é muito importante na decisäo a ser tomada e que no ato operatório deve ser feito inventário de todas as válvulas cardiácas, fontes possíveis de sépsis pós-operatória. Os autores apresentam, também baseados na experiência acumulada através dos anos, critérios maiores e menores para indicaçäo cirúrgica em endocardite infecciosa

Estenose congênita de traquéia: diagnóstico diferencial com anel vascular, relato de caso / Congenital trachecil stenosis: differential diagnosis with vascular ring. report of a case

Um menino de três anos de idade, com sinais de obstruçäo respiratória alta desde o nascimento foi submetido à ressecçäo do segmento traqueal estenótico resultando a cura. Ressalta-se a necessidade de estabelecer o diagnóstico diferenciawl entre os diferentes tipos de obstruçäo respiratória na infância. Sublinha-se a distinçäo entre estenose traqueal segmentar e anomalias do arco aórtico, estabelecida com o auxílio de traqueoscopia, aortografia e traqueografia. Descreve-se o tratamento efetuado

Papel da cirurgia no tratamento da endocardite infecciosa näo-próstética / Role of surgery in the treatment of non-prosthetic infective endocarditis

Onze pacientes con edocardite infecciosa foram revistos a partir da experiência dos autores nos dois últimos anos. A idade variou de 16 a 44 anos, näo havendo nítida prevalência quanto ao sexo ou à raça. A amior pare das hemoculturas era negativa. Os pacientes tinham prognóstico reservado, apresentando pelo menos duas ou três das indicaçöes cirúrgicas maiores estabelecidads na literatura. Apesar de o risco operatório ser alto, a mortalidade per-operatória foi de 0% e a pós-operatória de 18%. Em vista destes resultados, e da alta morbidade com o tratamento clínico isolado, recomendam uma conduta agressiva com a intervençäo cirurgica precoce, o que seguramente melhora em muito a sobrevida desses enfermos. Enfatizamos que o ecocardiograma é muito importante na decisäo a ser tomada, e que no ato operatório deve ser feito inventário de todas as válvulas cardíacas, fontes possíveis de sepsis pós-operatória