Prediction of pork quality parameters by applying fractals and data mining on MRI.

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate to excellent correlation coefficients were achieved by using the following combinations of acquisition sequences of MRI, fractal algorithms and data mining techniques: SE-FTA-MLR, SE-OPFTA-IR, GE-OPFTA-MLR, SE-OPFTA-MLR, with the last one offering the best prediction results. Thus, SE-OPFTA-MLR could be proposed as an alternative technique to determine physico-chemical traits of fresh and dry-cured loins in a non-destructive way with high accuracy.

Trigeminal nerve injury associated with injection of local anesthetics: needle lesion or neurotoxicity?

BACKGROUND: The authors used comprehensive national registry and clinical data to conduct a study of adverse drug reactions (ADRs), in particular neurosensory disturbance (NSD), associated with local anesthetics used in dentistry METHODS: The study included data sets of annual sales of local anesthetics (from 1995 through 2007), 292 reports to the Danish Medicines Agency, Copenhagen, Denmark, of adverse reactions to local anesthetic drugs, and a clinical sample of 115 patients with NSD associated with local anesthetics. The authors assessed lidocaine 2 percent, mepivacaine 2 percent and 3 percent, prilocaine 3 percent, and articaine 4 percent sold in cartridges. RESULTS: The study results showed a highly significant overrepresentation of NSDs associated with articaine 4 percent, in particular with mandibular blocks. CONCLUSIONS: The distribution of NSDs was disproportionate to the market share of three of the four drugs in both national registry data and clinical data. These findings indicate that the main cause of injury was neurotoxicity resulting from administration of the local anesthetic rather than the needle penetration. CLINICAL IMPLICATIONS: Clinicians may consider avoiding use of high-concentration (4 percent) anesthetic formulations for block anesthesia in the trigeminal area in cases in which there are viable alternatives.

Multispectral imaging for determination of astaxanthin concentration in salmonids.

Multispectral imaging has been evaluated for characterization of the concentration of a specific cartenoid pigment; astaxanthin. 59 fillets of rainbow trout, Oncorhynchus mykiss, were filleted and imaged using a rapid multispectral imaging device for quantitative analysis. The multispectral imaging device captures reflection properties in 19 distinct wavelength bands, prior to determination of the true concentration of astaxanthin. The samples ranged from 0.20 to 4.34 g per g fish. A PLSR model was calibrated to predict astaxanthin concentration from novel images, and showed good results with a RMSEP of 0.27. For comparison a similar model were built for normal color images, which yielded a RMSEP of 0.45. The acquisition speed of the multispectral imaging system and the accuracy of the PLSR model obtained suggest this method as a promising technique for rapid in-line estimation of astaxanthin concentration in rainbow trout fillets.

New approach for segmentation and quantification of two-dimensional gel electrophoresis images.

MOTIVATION: Detection of protein spots in two-dimensional gel electrophoresis images (2-DE) is a very complex task and current approaches addressing this problem still suffer from significant shortcomings. When quantifying a spot, most of the current software applications include a lot of background due to poor segmentation. Other software applications use a fixed window for this task, resulting in omission of part of the protein spot, or including background in the quantification. The approach presented here for the segmentation and quantification of 2-DE aims to minimize these problems. RESULTS: Five sections from different gels are used to test the performance of the presented method concerning the detection of protein spots, and three gel sections are used to test the quantification of sixty protein spots. Comparisons with a state-of-the-art commercial software and an academic state-of-the-art approach are presented. It is shown that the proposed approach for segmentation and quantification of 2-DE images can compete with the available commercial and academic software packages. AVAILABILITY: A command-line prototype may be downloaded, for non-commercial use, from http://w3.ualg.pt/~aanjos/prototypes.html.

Virtual dissection of pig carcasses.

This paper proposes the use of computed tomography (CT) as a reference method for estimating the lean meat percentage (LMP) of pig carcasses. The current reference is manual dissection which has a limited accuracy due to variability between butchers. A contextual Bayesian classification scheme is applied to classify volume elements of full body CT-scans of pig carcasses into three tissue types. A linear model describes the relation between voxels and the full weight of the half carcass, which can be determined more accurately than that of the lean meat content. Two hundred and ninety-nine half pig carcasses were weighed and CT-scanned. The explained variance of the model was R(2)=0.9994 with a root-mean-squared error of prediction of 83.6g. Applying this method as a reference will ensure a more robust calibration of sensors for measuring the LMP, which is less prone to variation induced by manual intervention.

A point-wise quantification of asymmetry using deformation fields: application to the study of the Crouzon mouse model.

This paper introduces a novel approach to quantify asymmetry in each point of a surface. The measure is based on analysing displacement vectors resulting from nonrigid image registration. A symmetric atlas, generated from control subjects is registered to a given subject image. A comparison of the resulting displacement vectors on the left and right side of the symmetry plane, gives a point-wise measure of asymmetry. The asymmetry measure was applied to the study of Crouzon syndrome using Micro CT scans of genetically modified mice. Crouzon syndrome is characterised by the premature fusion of cranial sutures, which gives rise to a highly asymmetric growth. Quantification and localisation of this asymmetry is of high value with respect to surgery planning and treatment evaluation. Using the proposed method, asymmetry was calculated in each point of the surface of Crouzon mice and wild-type mice (controls). Asymmetry appeared in similar regions for the two groups but the Crouzon mice were found significantly more asymmetric. The localisation ability of the method was in good agreement with ratings from a clinical expert. Validating the quantification ability is a less trivial task due to the lack of a gold standard. Nevertheless, a comparison with a different, but less accurate measure of asymmetry revealed good correlation.

Palatal surface area of maxillary plaster casts--a comparison between two-dimensional and three-dimensional measurements.

OBJECTIVE: To investigate the relationship between corresponding two-dimensional and three-dimensional measurements on maxillary plaster casts taken from photographs and three-dimensional surface scans, respectively. MATERIALS AND METHODS: Corresponding two-dimensional and three-dimensional measurements of selected linear distances, curve lengths, and (surface) areas were carried out on maxillary plaster casts from individuals with unilateral or bilateral cleft lip and palate. The relationship between two-dimensional and three-dimensional measurements was investigated using linear regression. RESULTS AND CONCLUSIONS: Error sources in the measurement of three-dimensional palatal segment surface area from a two-dimensional photograph were identified as photographic distortion (2.7%), interobserver error (3.3%), variability in the orientation of the plaster cast (3.2%), and natural shape variation (4.6%). The total error of determining the cleft area/palate surface area ratio was 15%. In population studies, the effect of using two-dimensional measurements is a decrease of discriminating power. In well-calibrated setups, a two-dimensional measurement of the cleft area/palate surface area ratio may be converted to a three-dimensional measurement by use of a multiplication factor of 0.75.

Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the Crouzon mutation Fgfr2(C342Y).

Crouzon syndrome is characterized by premature fusion of sutures and synchondroses. Recently, the first mouse model of the syndrome was generated, having the mutation Cys342Tyr in Fgfr2c, equivalent to the most common human Crouzon/Pfeiffer syndrome mutation. In this study, a set of micro-computed tomography (CT) scannings of the skulls of wild-type mice and Crouzon mice were analysed with respect to the dysmorphology caused by Crouzon syndrome. A computational craniofacial atlas was built automatically from the set of wild-type mouse micro-CT volumes using (1) affine and (2) non-rigid image registration. Subsequently, the atlas was deformed to match each subject from the two groups of mice. The accuracy of these registrations was measured by a comparison of manually placed landmarks from two different observers and automatically assessed landmarks. Both of the automatic approaches were within the interobserver accuracy for normal specimens, and the non-rigid approach was within the interobserver accuracy for the Crouzon specimens. Four linear measurements, skull length, height and width and interorbital distance, were carried out automatically using the two different approaches. Both automatic approaches assessed the skull length, width and height accurately for both groups of mice. The non-rigid approach measured the interorbital distance accurately for both groups while the affine approach failed to assess this parameter for both groups. Using the full capability of the non-rigid approach, local displacements obtained when registering the non-rigid wild-type atlas to a non-rigid Crouzon mouse atlas were determined on the surface of the wild-type atlas. This revealed a 0.6-mm bending in the nasal region and a 0.8-mm shortening of the zygoma, which are similar to characteristics previously reported in humans. The most striking finding of this analysis was an angulation of approximately 0.6 mm of the cranial base, which has not been reported in humans. Comparing the two different methodologies, it is concluded that the non-rigid approach is the best way to assess linear skull parameters automatically. Furthermore, the non-rigid approach is essential when it comes to analysing local, non-linear shape differences.

A method for comparison of growth media in objective identification of Penicillium based on multi-spectral imaging.

We consider the problems of using excessive growth media for identification and performing objective identification of fungi at the species level. We propose a method for choosing the subset of growth media, which provides the best discrimination between several fungal species. Furthermore, we propose the use of multi-spectral imaging as a means of objective identification. Three species of the fungal genus Penicillium are subject to classification. To obtain an objective classification we use multi-spectral images. Previously, RGB images have proven useful for the purpose. We use multi-spectral bands as they provide additional information about the chemistry of the fungal colonies. In this study three media [Czapek yeast extract agar (CYA), oatmeal agar (OAT), and yeast extract sucrose agar (YES)] have been compared on their ability to discriminate between the three species. We propose a statistical method to test which medium or combination of media gives the best discrimination. Statistical tests indicate that YES combined with CYA is the best choice of media in this case. However, for the objective identification one medium is sufficient to discriminate between the species. Statistical tests show that there are significant differences between the species on all individual media, and that these differences are largest on YES. The objective identification has been performed solely by means of digital image analysis. The features obtained from the image analysis merely correspond to macro-morphological features. The species have been classified using only 3-4 of the spectral bands with a 100% correct classification rate using both leave-one-out cross-validation and test set validation.

FAME--a flexible appearance modeling environment.

Combined modeling of pixel intensities and shape has proven to be a very robust and widely applicable approach to interpret images. As such the active appearance model (AAM) framework has been applied to a wide variety of problems within medical image analysis. This paper summarizes AAM applications within medicine and describes a public domain implementation, namely the flexible appearance modeling environment (FAME). We give guidelines for the use of this research platform, and show that the optimization techniques used renders it applicable to interactive medical applications. To increase performance and make models generalize better, we apply parallel analysis to obtain automatic and objective model truncation. Further, two different AAM training methods are compared along with a reference case study carried out on cross-sectional short-axis cardiac magnetic resonance images and face images. Source code and annotated data sets needed to reproduce the results are put in the public domain for further investigation.

Diagnostic decision rule for support in clinical assessment of the need for surgical intervention in horses with acute abdominal pain.

A prospective survey of horses with colic referred to a university hospital was undertaken to elaborate on a simple clinical decision support system capable of predicting whether or not horses require surgical intervention. Cases were classified as requiring surgical intervention or not on the basis of intraoperative findings or necropsy reports. Logistic regression analysis was applied to identify predictors with the strongest association with treatment needed. The classification and regression tree (CART) methodology was used to combine the variables in a simple classification system. The performance of the elaborated algorithms, as diagnostic instruments, was recorded as test sensitivity and specificity. The CART method generated 5 different classification trees with a similar basic structure consisting of: degree of pain, peritoneal fluid colour, and rectal temperature. The tree, constructed at a prevalence of 15% surgical cases, appeared to be the best proposal made by CART. In this classification tree, further discrimination of cases was obtained by including the findings of rectal examination and packed cell volume. When regarded as a test system, the sensitivity and specificity was 52% and 95%, respectively, corresponding to positive and negative predictive values of 68% and 91%. The variables examined in the present study did not provide a safe clinical decision rule. The classification tree constructed at 15% surgical cases was considered feasible, the proportion of horses incorrectly predicted to be without need of immediate surgery (false negatives) was small, whereas the proportion of horses incorrectly predicted to be in need of immediate surgery (false positives) was large. Some of the false positive horses were amenable to surgical treatment, although these cases did not conform to the strict definition of a surgical case. A less rigorous definition of a surgical case than that used in the present study would lower the percentage of false positives.