Algorithms for automatic segmentation of bovine embryos produced

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.

Segmentation of Cell Nuclei Regions in Epithelium of Prostate Glands

This paper proposes a method for segmentation of cell nuclei regions in epithelium of prostate glands. This structure provides information to diagnosis and prognosis of prostate cancer. In the initial step, the contrast stretching technique was applied in image in order to improve the contrast between regions of interest and other regions. After, the global thresholding technique was applied and the value of threshold was defined empirically. Finally, the false positive regions were removed using the connected components technique. The performance of the proposed method was compared with the Otsu technique and statistical measures of accuracy were calculated based on reference images (gold standard). The result of the mean value of accuracy of proposed method was 93% ± 0.07.

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.

Image segmentation using morphological watershed applied to cartography

Image segmentation is a process frequently used in several different areas including Cartography. Feature extraction is a very troublesome task, and successful results require more complex techniques and good quality data. The aims of this paper is to study Digital Image Processing techniques, with emphasis in Mathematical Morphology, to use Remote Sensing imagery, making image segmentation, using morphological operators, mainly the multi-scale morphological gradient operator. In the segmentation process, pre-processing operators of Mathematical Morphology were used, and the multi-scales gradient was implemented to create one of the images used as marker image. Orbital image of the Landsat satellite, sensor TM was used. The MATLAB software was used in the implementation of the routines. With the accomplishment of tests, the performance of the implemented operators was verified and carried through the analysis of the results. The extration of linear feature, using mathematical morphology techniques, can contribute in cartographic applications, as cartographic products updating. The comparison to the best result obtained was performed by means of the morphology with conventional techniques of features extraction. © Springer-Verlag 2004.

The increase of dairy intake is the main dietary factor associated with reduction of body weight in overweight adults after lifestyle change program

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Changes in malondialdehyde and C-reactive protein concentrations after lifestyle modification are related to different metabolic syndrome-associated pathophysiological processes

Metabolic syndrome (MetS) is often accompanied by pro-oxidative and pro-inflammatory processes. Lifestyle modification (LiSM) may act as primary treatment for these processes. This study aimed to elucidate influencing factors on changes of malondialdehyde (MDA) and C-reactive protein (CRP) concentrations after a LiSM intervention. Sixty subjects (53 yrs, 84% women) clinically approved to attend a 20 weeks LiSM-program were submitted to weekly nutritional counseling and physical activities combining aerobic (3 times/week) and resistance (2 times/week) exercises. Before and after intervention they were assessed for anthropometric, clinical, cardiorespiratory fitness test (CRF) and laboratory markers. Statistical analyses performed were multiple regression analysis and backward stepwise with p<0.05 and R(2) as influence index. LiSM was responsible for elevations in CRF, healthy eating index (HEI), total plasma antioxidant capacity (TAP) and HDL-C along with reductions in waist circumference measures and MetS (47-40%) prevalence. MDA and CRP did not change after LiSM, however, we observed that MDA concentrations were positively influenced (R(2)=0.35) by fasting blood glucose (β=0.64) and HOMA-IR (β=0.58) whereas CRP concentrations were by plasma gamma-glutamyltransferase activity (β=0.54; R(2)=0.29). Pro-oxidant and pro-inflammatory states of MetS can be attenuated after lifestyle modification if glucose metabolism homeostasis were recovered and if liver inflammation were reduced, respectively.

WITHDRAWN: The increase of dairy intake is the main dietary factor associated with reduction of body weight in overweight adults after lifestyle change program

This article has been withdrawn at the request of the author(s) and editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.

Omega-3 fatty acids supplementation decreases metabolic syndrome prevalence after lifestyle modification program

The additional effect of omega-3 supplementation in association with lifestyle modification program (LSMP) in free living-adults was evaluated.We studied 39 adults (control group with LSMP (G1, n = 16) and LSMP plus supplementation of 3 g of fish oil per day (360 mg of docosahexaenoic acid and 540 mg of eicosapentaenoic acid) (G2, n = 23)) during 20 weeks. The fish oil group showed a significant decrease in waist circumference (1.3%) followed by metabolic syndrome reduction (29%) mainly due to normalization of blood pressure (33.3%) and triacylglycerol (27.3%). Omega-3 supplementation provided additional benefits to LSMP in the resolution of metabolic syndrome

Dietary intake association with IFG and responses of a lifestyle changing protocol in a community-b based adult cohort

Objective: Investigate the association of diet on Impaired Fasting Glucose (IFG) and response of a lifestyle changing protocol (LISC) on a community sample of adults. Methods: A cross sectional study of LISC was conducted with 1004 subjects. From those, 264 adults individuals participated in a 20-week intervention based on physical exercises and dietary counseling and were divided in three groups, normoglycemic, IFG, and T2DM. Evaluations were done at baseline (M0) and after a 20-week intervention (M1). The analyses were performed by using SAS, version 9.2., and results were discussed based on the level of significance of p<0.05. Results: At baseline, the three groups differed for plasma triglycerides, and number of altered metabolic syndrome (MetS) components. T2DM differed from normoglicemic by presenting higher intake of meat, lower of sugar, and less dietary variety, along with higher plasma levels of uric acid. After 20-week intervention, normoglicemics, IFG and T2DM responded similarly to LISC. Both genders increased body fatness. Men increased fasting plasma insulin, saturated fatty acid intake, along with a decrease of vegetable oil intake while women showed a significant increase in HEI and dietary fiber intake and a trend to higher sugar and protein intake and lower vegetable oil intake. Overall T2DM decreased 68% from M0 (9.5%) to M1 (6.4%) of LISC. Conclusion: Our data showed a significant difference in food composition on altered plasma glucose, and its further normalization with lifestyle intervention was independent of significant body weight and body fat changes.

Behavioral risk factors and effects of lifestyle modification on adults with diabetes: a Brazilian community-based study

Lifestyle is directly related to the incidence of type 2 diabetes mellitus (DM-2), a risk dramatically elevated by obesity and inactivity. Several studies have verified that educational interventions can delay the onset of DM-2. Some of the interventions strategies utilized medication and diet, diet and/or physical exercise or the combination of diet and exercise, generally referred to a change in lifestyle. Despite the evidence that DM-2 can be preventive, there is still limited availability of effective prevention programs. DM-2 is considered an emerging public health problem as it is estimated that by the year of 2030 there will be about 366 million people with diabetes worldwide. DM2 remains a leading cause of cardiovascular disorders and many other complications. Our intent with this paper is to present researches and strategies (diet and physical activity interventions) that successfully improved plasma glucose control as a result of an effective lifestyle intervention program.

Metformin versus lifestyle changes in treating women with polycystic ovary syndrome

Objective: To compare the efficacy of metformin with that of lifestyle changes in patients with polycystic ovary syndrome (PCOS). Design: Prospective, randomized clinical trial of 40 women with PCOS to analyze the effects of metformin and lifestyle intervention treatments on menstrual pattern and hormone and metabolic profile. The duration of treatment was 6 months. Statistical analysis was done using Student's t-test. Results: Fifteen women in the metformin group and 12 in the lifestyle changes group completed the study. The menstrual pattern improved by similar to 67% in both groups. There was a significant decrease in waist circumference in the lifestyle changes group (101.8 +/- 3.9 and 95.1 +/- 3.6, at baseline and at 6 months of treatment, respectively; p<0.001) and in body mass index (BMI) in both groups. The predictor of menstrual pattern improvement was BMI. Conclusions: Both metformin and lifestyle changes may increase the number of menstrual cycles in PCOS. This effect was related to a decrease in BMI.

Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.