Threading libraries performance when applied to image acquisition and processing in a forensic application

Peer-reviewed

Body image perception and weight-related behaviour among adolescents of the Seychelles

Background: We examined one's own body image perception and its association with reported weight-related behavior among adolescents of a rapidly developing country in the African region. Methods: We conducted a school-based survey of 1432 students aged 11-17 years in the Seychelles. Weight and height were measured, and thinness, normal weight and overweight were assessed along standard criteria. A self-administered and anonymous questionnaire was administered. Perception of body image was assessed using both a closed-ended question (CEQ) and the Stunkard's pictorial silhouettes (SPS). Finally, a question assessed voluntary attempts to change weight. Results: Overall, 14.1% of the students were thin, 63.9% were normal-weight, and 22.0% were overweight or obese. There was fair agreement between actual weight status and self-perceived body image based on either CEQ or SPS. However, a substantial proportion of the overweight students did not consider themselves as overweight (SPS: 24%, CEQ: 34%) and, inversely, a substantial proportion of the normal-weight students considered themselves as too thin (SPS: 29%, CEQ: 15%). Among the overweight students, an adequate attempt to lose weight was reported more often by boys and girls who perceived themselves as overweight vs. not overweight (72-88% vs. 40-71%, p <0.05 for most comparisons). Among the normal-weight students, an inadequate attempt to gain weight was reported more often by boys and girls who perceived themselves as thin vs. not thin (27-68% vs. 11-19%, p <0.05). Girls had leaner own body ideals than boys. Conclusions: We found that substantial proportions of overweight students did not perceive themselves as overweight and/or did not want to lose weight and, inversely, that many normalweight students perceived themselves as too thin and/or wanted to gain weight: this points to forces that can drive the upwards overweight trends. Appropriate perception of one's weight was associated with adequate weight-control behavior, although not strongly, emphasizing that appropriate weight perception is only one of several factors driving adequate weight-related behavior. These findings emphasize the need to address appropriate perception of one's own weight and adequate weight-related behavior in adolescents for both individual and community weight-related interventions.

Fructose Rich Diet-Induced High Plasminogen Activator Inhibitor-1 (PAI-1) Production in the Adult Female Rat: Protective Effect of Progesterone.

The effect of progesterone (P4) on fructose rich diet (FRD) intake-induced metabolic, endocrine and parametrial adipose tissue (PMAT) dysfunctions was studied in the adult female rat. Sixty day-old rats were i.m. treated with oil alone (control, CT) or containing P4 (12 mg/kg). Rats ate Purina chow-diet ad libitum throughout the entire experiment and, between 100 and 120 days of age drank ad libitum tap water alone (normal diet; CT-ND and P4-ND) or containing fructose (10% w/v; CT-FRD and P4-FRD). At age 120 days, animals were subjected to a glucose tolerance test or decapitated. Plasma concentrations of various biomarkers and PMAT gene abundance were monitored. P4-ND (vs. CT-ND) rats showed elevated circulating levels of lipids. CT-FRD rats displayed high (vs. CT-ND) plasma concentrations of lipids, leptin, adiponectin and plasminogen activator inhibitor-1 (PAI-1). Lipidemia and adiponectinemia were high (vs. P4-ND) in P4-FRD rats. Although P4 failed to prevent FRD-induced hyperleptinemia, it was fully protective on FRD-enhanced plasma PAI-1 levels. PMAT leptin and adiponectin mRNAs were high in CT-FRD and P4-FRD rats. While FRD enhanced PMAT PAI-1 mRNA abundance in CT rats, this effect was absent in P4 rats. Our study supports that a preceding P4-enriched milieu prevented the enhanced prothrombotic risk induced by FRD-elicited high PAI-1 production.

Computer-aided volume measurement of posttraumatic orbits reconstructed with AO titanium mesh plates: accuracy and reliability

PURPOSE: To prospectively evaluate the accuracy and reliability of "freehand" posttraumatic orbital wall reconstruction with AO (Arbeitsgemeinschaft Osteosynthese) titanium mesh plates by using computer-aided volumetric measurement of the bony orbits. METHODS: Bony orbital volume was measured in 12 patients from coronal CT scan slices using OsiriX Medical Image software. After defining the volumetric limits of the orbit, the segmentation of the bony orbital region of interest of each single slice was performed. At the end of the segmentation process, all regions of interest were grouped and the volume was computed. The same procedure was performed on both orbits, and thereafter the volume of the contralateral uninjured orbit was used as a control for comparison. RESULTS: In all patients, the volume data of the reconstructed orbit fitted that of the contralateral uninjured orbit with accuracy to within 1.85 cm3 (7%). CONCLUSIONS: This preliminary study has demonstrated that posttraumatic orbital wall reconstruction using "freehand" bending and placement of AO titanium mesh plates results in a high success rate in re-establishing preoperative bony volume, which closely approximates that of the contralateral uninjured orbit.

An Image Enhancement Technique using MTF of Human eye

Image filtering is a highly demanded approach of image enhancement in digital imaging systems design. It is widely used in television and camera design technologies to improve the quality of an output image to avoid various problems such as image blurring problem thatgains importance in design of displays of large sizes and design of digital cameras. This thesis proposes a new image filtering method basedon visual characteristics of human eye such as MTF. In contrast to the traditional filtering methods based on human visual characteristics this thesis takes into account the anisotropy of the human eye vision. The proposed method is based on laboratory measurements of the human eye MTF and takes into account degradation of the image by the latter. This method improves an image in the way it will be degraded by human eye MTF to give perception of the original image quality. This thesis gives a basic understanding of an image filtering approach and the concept of MTF and describes an algorithm to perform an image enhancement based on MTF of human eye. Performed experiments have shown quite good results according to human evaluation. Suggestions to improve the algorithm are also given for the future improvements.

Potential role for peroxisome proliferator activated receptor (PPAR) in preventing colon cancer.

BACKGROUND: Peroxisome proliferator activated receptors (PPARs) are nuclear hormone receptors involved in genetic control of many cellular processes. PPAR and PPAR have been implicated in colonic malignancy. Here we provide three lines of evidence suggesting an inhibitory role for PPAR in colorectal cancer development. METHODS: Levels of PPAR mRNA and protein in human colorectal cancers were compared with matched non-malignant mucosa using RNAse protection and western blotting. APC(Min)/+ mice were randomised to receive the PPAR activator methylclofenapate 25 mg/kg or vehicle for up to 16 weeks, and small and large intestinal polyps were quantified by image analysis. The effect of methylclofenapate on serum stimulated mitogenesis (thymidine incorporation), linear cell growth, and annexin V and propidium iodide staining were assessed in human colonic epithelial cells. RESULTS: PPAR (mRNA and protein) expression levels were significantly depressed in colorectal cancer compared with matched non-malignant tissue. Methylclofenapate reduced polyp area in the small intestine from 18.7 mm(2) (median (interquartile range 11.1, 26.8)) to 9.90 (4.88, 13.21) mm(2) (p=0.003) and in the colon from 9.15 (6.31, 10.5) mm(2) to 3.71 (2.71, 5.99) mm(2) (p=0.009). Methylclofenapate significantly reduced thymidine incorporation and linear cell growth with no effect on annexin V or propidium iodide staining. CONCLUSIONS: PPAR may inhibit colorectal tumour progression, possibly via inhibition of proliferation, and may be an important therapeutic target.

Three-Dimensional (3D) Microarchitecture Correlations with 2D Projection Image Gray-Level Variations Assessed by Trabecular Bone Score Using High-Resolution Computed Tomographic Acquisitions: Effects of Resolution and Noise.

The aim of the present study is to determine the level of correlation between the 3-dimensional (3D) characteristics of trabecular bone microarchitecture, as evaluated using microcomputed tomography (μCT) reconstruction, and trabecular bone score (TBS), as evaluated using 2D projection images directly derived from 3D μCT reconstruction (TBSμCT). Moreover, we have evaluated the effects of image degradation (resolution and noise) and X-ray energy of projection on these correlations. Thirty human cadaveric vertebrae were acquired on a microscanner at an isotropic resolution of 93μm. The 3D microarchitecture parameters were obtained using MicroView (GE Healthcare, Wauwatosa, MI). The 2D projections of these 3D models were generated using the Beer-Lambert law at different X-ray energies. Degradation of image resolution was simulated (from 93 to 1488μm). Relationships between 3D microarchitecture parameters and TBSμCT at different resolutions were evaluated using linear regression analysis. Significant correlations were observed between TBSμCT and 3D microarchitecture parameters, regardless of the resolution. Correlations were detected that were strongly to intermediately positive for connectivity density (0.711≤r(2)≤0.752) and trabecular number (0.584≤r(2)≤0.648) and negative for trabecular space (-0.407 ≤r(2)≤-0.491), up to a pixel size of 1023μm. In addition, TBSμCT values were strongly correlated between each other (0.77≤r(2)≤0.96). Study results show that the correlations between TBSμCT at 93μm and 3D microarchitecture parameters are weakly impacted by the degradation of image resolution and the presence of noise.

Sparse image reconstruction on the sphere: implications of a new sampling theorem.

We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to improve the fidelity of sparse image reconstruction, through both the dimensionality and sparsity of signals. To demonstrate this result, we consider a simple inpainting problem on the sphere and consider images sparse in the magnitude of their gradient. We develop a framework for total variation inpainting on the sphere, including fast methods to render the inpainting problem computationally feasible at high resolution. Recently a new sampling theorem on the sphere was developed, reducing the required number of samples by a factor of two for equiangular sampling schemes. Through numerical simulations, we verify the enhanced fidelity of sparse image reconstruction due to the more efficient sampling of the sphere provided by the new sampling theorem.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Retinal Image Analysis Using Machine Vision

The topic of this thesis is studying how lesions in retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. Methods for equalizing uneven illumination in fundus images, detecting regions of poor image quality due toinadequate illumination, and recognizing abnormal lesions were developed duringthe work. The developed methods exploit mainly the color information and simpleshape features to detect lesions. In addition, a graphical tool for collecting lesion data was developed. The tool was used by an ophthalmologist who marked lesions in the images to help method development and evaluation. The tool is a general purpose one, and thus it is possible to reuse the tool in similar projects.The developed methods were tested with a separate test set of 128 color fundus images. From test results it was calculated how accurately methods classify abnormal funduses as abnormal (sensitivity) and healthy funduses as normal (specificity). The sensitivity values were 92% for hemorrhages, 73% for red small dots (microaneurysms and small hemorrhages), and 77% for exudates (hard and soft exudates). The specificity values were 75% for hemorrhages, 70% for red small dots, and 50% for exudates. Thus, the developed methods detected hemorrhages accurately and microaneurysms and exudates moderately.

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Endovascular coiling compared with surgical clipping for the treatment of unruptured middle cerebral artery aneurysms: an update.

OBJECT: In 1999 we reported that 94% of unruptured middle cerebral artery (MCA) aneurysms managed prospectively between 1993 and 1997, according to a protocol favoring endovascular coiling, were best treated by surgical clipping. The goal of the current study was to delineate the most appropriate treatment option for unruptured MCA aneurysms today, considering the technical advances in imaging and in endovascular treatment. METHODS: 35 consecutive patients harboring 40 unruptured MCA aneurysms were treated between 1997 and December 2000. Patients with unruptured cerebral aneurysms are managed prospectively according to the same protocol as reported previously [1]: the primary treatment recommendation is endovascular packing with Guglielmi detachable coils (GDCs). Surgical clipping is recommended after failed attempt at coil placement or in the presence of angioanatomical features that contraindicate that type of endovascular therapy. RESULTS: One unruptured MCA aneurysm was treated by endovascular embolization, 37 unruptured MCA aneurysms were clipped, whereas 2 unruptured MCA aneurysms were trapped with simultaneous extracranial-intracranial revascularization. Postoperative angiography revealed complete exclusion of all aneurysms. Preservation of vascular permeability was demonstrated in all clip-reconstructed aneurysms, despite arterial branches frequently originating from the aneurysmal base. Cerebral revascularization of the distal MCA was successful in the 2 patients with giant aneurysms. None of the patients presented permanent disabling complications from the treatment of the unruptured MCA aneurysm. CONCLUSION: Despite major technical advances in imaging and in endovascular treatment of cerebral aneurysms, surgical clipping still is the most efficient treatment for unruptured MCA aneurysms at the beginning of the new millennium.