Some Items to Consider Before You Change the Calving Season of Your Beef Cow Herd

This publication gives important items to consider before changing calving seasons of beef cow herds

Using Pareto Fronts to Evaluate Polyp Detection Algorithms for CT Colonography

We evaluate and improve an existing curvature-based region growing algorithm for colonic polyp detection for our CT colonography (CTC) computer-aided detection (CAD) system by using Pareto fronts. The performance of a polyp detection algorithm involves two conflicting objectives, minimizing both false negative (FN) and false positive (FP) detection rates. This problem does not produce a single optimal solution but a set of solutions known as a Pareto front. Any solution in a Pareto front can only outperform other solutions in one of the two competing objectives. Using evolutionary algorithms to find the Pareto fronts for multi-objective optimization problems has been common practice for years. However, they are rarely investigated in any CTC CAD system because the computation cost is inherently expensive. To circumvent this problem, we have developed a parallel program implemented on a Linux cluster environment. A data set of 56 CTC colon surfaces with 87 proven positive detections of polyps sized 4 to 60 mm is used to evaluate an existing one-step, and derive a new two-step region growing algorithm. We use a popular algorithm, the Strength Pareto Evolutionary Algorithm (SPEA2), to find the Pareto fronts. The performance differences are evaluated using a statistical approach. The new algorithm outperforms the old one in 81.6% of the sampled Pareto fronts from 20 simulations. When operated at a suitable sensitivity level such as 90.8% (79/87) or 88.5% (77/87), the FP rate is decreased by 24.4% or 45.8% respectively

Wavelet Analysis in Virtual Colonoscopy

The computed tomographic colonography (CTC) computer aided detection (CAD) program is a new method in development to detect colon polyps in virtual colonoscopy. While high sensitivity is consistently achieved, additional features are desired to increase specificity. In this paper, a wavelet analysis was applied to CTCCAD outputs in an attempt to filter out false positive detections. 52 CTCCAD detection images were obtained using a screen capture application. 26 of these images were real polyps, confirmed by optical colonoscopy and 26 were false positive detections. A discrete wavelet transform of each image was computed with the MATLAB wavelet toolbox using the Haar wavelet at levels 1-5 in the horizontal, vertical and diagonal directions. From the resulting wavelet coefficients at levels 1-3 for all directions, a 72 feature vector was obtained for each image, consisting of descriptive statistics such as mean, variance, skew, and kurtosis at each level and orientation, as well as error statistics based on a linear predictor of neighboring wavelet coefficients. The vectors for each of the 52 images were then run through a support vector machine (SVM) classifier using ten-fold cross-validation training to determine its efficiency in distinguishing polyps from false positives. The SVM results showed 100% sensitivity and 51% specificity in correctly identifying the status of detections. If this technique were added to the filtering process of the CTCCAD polyp detection scheme, the number of false positive results could be reduced significantly

Validating Pareto Optimal Operation Parameters of Polyp Detection Algorithms for CT Colonography

We evaluated a Pareto front-based multi-objective evolutionary algorithm for optimizing our CT colonography (CTC) computer-aided detection (CAD) system. The system identifies colonic polyps based on curvature and volumetric based features, where a set of thresholds for these features was optimized by the evolutionary algorithm. We utilized a two-fold cross-validation (CV) method to test if the optimized thresholds can be generalized to new data sets. We performed the CV method on 133 patients; each patient had a prone and a supine scan. There were 103 colonoscopically confirmed polyps resulting in 188 positive detections in CTC reading from either the prone or the supine scan or both. In the two-fold CV, we randomly divided the 133 patients into two cohorts. Each cohort was used to obtain the Pareto front by a multi-objective genetic algorithm, where a set of optimized thresholds was applied on the test cohort to get test results. This process was repeated twice so that each cohort was used in the training and testing process once. We averaged the two training Pareto fronts as our final training Pareto front and averaged the test results from the two runs in the CV as our final test results. Our experiments demonstrated that the averaged testing results were close to the mean Pareto front determined from the training process. We conclude that the Pareto front-based algorithm appears to be generalizable to new test data

Exogenous glucagon-like peptide-1 attenuates the glycaemic response to postpyloric nutrient infusion in critically ill patients with type-2 diabetes

Extent: 11p.Introduction: Glucagon-like peptide-1 (GLP-1) attenuates the glycaemic response to small intestinal nutrient infusion in stress-induced hyperglycaemia and reduces fasting glucose concentrations in critically ill patients with type-2 diabetes. The objective of this study was to evaluate the effects of acute administration of GLP-1 on the glycaemic response to small intestinal nutrient infusion in critically ill patients with pre-existing type-2 diabetes. Methods: Eleven critically ill mechanically-ventilated patients with known type-2 diabetes received intravenous infusions of GLP-1 (1.2 pmol/kg/minute) and placebo from t = 0 to 270 minutes on separate days in randomised double-blind fashion. Between t = 30 to 270 minutes a liquid nutrient was infused intraduodenally at a rate of 1 kcal/min via a naso-enteric catheter. Blood glucose, serum insulin and C-peptide, and plasma glucagon were measured. Data are mean ± SEM. Results: GLP-1 attenuated the overall glycaemic response to nutrient (blood glucose AUC30-270 min: GLP-1 2,244 ± 184 vs. placebo 2,679 ± 233 mmol/l/minute; P = 0.02). Blood glucose was maintained at < 10 mmol/l in 6/11 patients when receiving GLP-1 and 4/11 with placebo. GLP-1 increased serum insulin at 270 minutes (GLP-1: 23.4 ± 6.7 vs. placebo: 16.4 ± 5.5 mU/l; P < 0.05), but had no effect on the change in plasma glucagon. Conclusions: Exogenous GLP-1 in a dose of 1.2 pmol/kg/minute attenuates the glycaemic response to small intestinal nutrient in critically ill patients with type-2 diabetes. Given the modest magnitude of the reduction in glycaemia the effects of GLP-1 at higher doses and/or when administered in combination with insulin, warrant evaluation in this group.Adam M Deane, Matthew J Summers, Antony V Zaknic, Marianne J Chapman, Robert JL Fraser, Anna E Di Bartolomeo, Judith M Wishart, Michael Horowit