Autoencoding the Retrieval Relevance of Medical Images

Content-based image retrieval (CBIR) of medical images is a crucial task that can contribute to a more reliable diagnosis if applied to big data. Recent advances in feature extraction and classification have enormously improved CBIR results for digital images. However, considering the increasing accessibility of big data in medical imaging, we are still in need of reducing both memory requirements and computational expenses of image retrieval systems. This work proposes to exclude the features of image blocks that exhibit a low encoding error when learned by a $n/p/n$ autoencoder ($p\!<\!n$). We examine the histogram of autoendcoding errors of image blocks for each image class to facilitate the decision which image regions, or roughly what percentage of an image perhaps, shall be declared relevant for the retrieval task. This leads to reduction of feature dimensionality and speeds up the retrieval process. To validate the proposed scheme, we employ local binary patterns (LBP) and support vector machines (SVM) which are both well-established approaches in CBIR research community. As well, we use IRMA dataset with 14,410 x-ray images as test data. The results show that the dimensionality of annotated feature vectors can be reduced by up to 50% resulting in speedups greater than 27% at expense of less than 1% decrease in the accuracy of retrieval when validating the precision and recall of the top 20 hits.Comment: To appear in proceedings of The 5th International Conference on Image Processing Theory, Tools and Applications (IPTA'15), Nov 10-13, 2015, Orleans, Franc

Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data

Good results on image classification and retrieval using support vector machines (SVM) with local binary patterns (LBPs) as features have been extensively reported in the literature where an entire image is retrieved or classified. In contrast, in medical imaging, not all parts of the image may be equally significant or relevant to the image retrieval application at hand. For instance, in lung x-ray image, the lung region may contain a tumour, hence being highly significant whereas the surrounding area does not contain significant information from medical diagnosis perspective. In this paper, we propose to detect salient regions of images during training and fold the data to reduce the effect of irrelevant regions. As a result, smaller image areas will be used for LBP features calculation and consequently classification by SVM. We use IRMA 2009 dataset with 14,410 x-ray images to verify the performance of the proposed approach. The results demonstrate the benefits of saliency-based folding approach that delivers comparable classification accuracies with state-of-the-art but exhibits lower computational cost and storage requirements, factors highly important for big data analytics.Comment: To appear in proceedings of The 14th International Conference on Machine Learning and Applications (IEEE ICMLA 2015), Miami, Florida, USA, 201

Apparent histological changes of adipocytes after treatment with CL 316,243, a β-3-adrenergic receptor agonist

Background and objectives: The objective of this experiment was to study the effect of CL 316,243 (CL) (a highly selective β3-adrenergic receptor agonist) on cellular changes occurring in retroperitoneal white adipose tissue (RWAT) of lean and obese rats.Methods: Ten-month-old lean and obese Zucker rats were implanted subcutaneously with osmotic mini-pumps, infusing either saline or CL (1 mg/kg body weight/day) for 4 weeks. Results: There was no effect of CL on food intake. However, the resting metabolic rate in lean and obese rats increased by 55 and 96 per rat, respectively. Total RWAT weight decreased in both lean and obese rats under influence of CL treatment by 65 and 38, respectively. Total body weight and body fat were lower in CL treated rats. Detection of uncoupling protein 1 (UCP1) in RWAT was confirmed qualitatively by both immunohistochemistry and immunofluorescence using a rabbit anti rat UCP1 antibody which showed the appearance of a marked increase of this protein in the adipose tissue. Stained semi-thin sections (0.5 µm) also demonstrated abundant nuclei in multilocular adipocytes, in endothelial cells associated with the vasculature, and in interstitial cells. In CL-treated obese rats, a clustering of several multilocular cells around the periphery of a white adipocyte was seen.Conclusion: These results indicate that treatment of both lean and obese Zucker rats with CL induces extensive remodeling of RWAT that includes shrinkage of white adipose tissue, appearance of abundant multilocular cells in RWAT together with the appearance of a marked increase of UCP, preferentially in lean rats. © 2015 Ghorbani et al

Norms of anthropometric, body composition measures and prevalence of overweight and obesity in urban populations of Iran

زمینه و هدف: تدوین هنجارهای ملی برای اندازه‌های پیکری و ترکیب بدنی و نیز تعیین شیوع اضافه وزن و چاقی به دلیل ارتباط آن با بیماری‌های مزمن از ضروریات جوامع امروزی است. این پژوهش با هدف تهیه‌ی این هنجارها در جمعیت‌های شهری ایران طراحی و اجرا شد. روش بررسی: در این پژوهش مقطعی که از نوع توصیفی – تحلیلی بود، 991 نفر مرد و 1188 نفر زن با دامنه سنی 15 تا 64 سال به شیوه در دسترس از شهرهای اردبیل، اصفهان، اهواز، تهران، رشت، کرمان و مشهد فراخوان شدند. شاخص توده‌ی بدن (BMI)، دور کمر (WC)، نسبت دور کمر به لگن (WHR)، نسبت دور کمر به قد (WHtR) و درصد چربی بدن آزمودنی‌ها اندازه‌گیری شد. داده ها با استفاده از آزمون های t مستقل، ضریب همبستگی جزیی تعدیل شده و تحلیل واریانس یک طرفه در نرم افزار SPSS تجزیه و تحلیل شدند. یافته‌ها: با توجه به اندازه‌های BMI، 49 مردان و 53 زنان دارای اضافه وزن یا چاقی بودند که 2/10 مردان و 6/18 زنان چاق بودند. در هر گروه سنی، مردان درصد چربی کمتری نسبت به زنان داشتند (001/0>P). در هر دوی مردان و زنان شیوع اضافه وزن در میان رده‌ی سنی 49-40 سال و شیوع چاقی در رده‌ی سنی بالای 50 سال بیشتر از سنین دیگر بود. نتیجه‌گیری: یافته‌های پژوهش حاضر ضمن ارایه‌ی هنجارهای ملی، شیوع بالای اضافه وزن و چاقی عمومی و شکمی را در هر دو جنسیت در جمعیت‌های شهری ایران نشان داد که بیانگر لزوم ارزیابی‌های مستمر و ارایه‌ی برنامه‌های مداخله‌ای در جهت کنترل و پیشگیری از اختلال‌های مرتبط با چاقی مانند دیابت می‌باش

A stochastic vortex structure method for interacting particles in turbulent shear flows

In a recent study, we have proposed a new synthetic turbulence method based on stochastic vortex structures (SVSs), and we have demonstrated that this method can accurately predict particle transport, collision, and agglomeration in homogeneous, isotropic turbulence in comparison to direct numerical simulation results. The current paper extends the SVS method to non-homogeneous, anisotropic turbulence. The key element of this extension is a new inversion procedure, by which the vortex initial orientation can be set so as to generate a prescribed Reynolds stress field. After validating this inversion procedure for simple problems, we apply the SVS method to the problem of interacting particle transport by a turbulent planar jet. Measures of the turbulent flow and of particle dispersion, clustering, and collision obtained by the new SVS simulations are shown to compare well with direct numerical simulation results. The influence of different numerical parameters, such as number of vortices and vortex lifetime, on the accuracy of the SVS predictions is also examined

On the Variability of Mesospheric OH Emission Profiles

Mesospheric OH radiance limb profiles measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument aboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) spacecraft were inverted to yield altitude profiles of OH volume emission rates. The Abel inversion results of two months of data (from 1 June to 31 July 2004) were analyzed for the layer mean and standard deviation as a function of latitude and local time. Statistical analysis of SABER data shows that the global difference between the mean and standard deviation profiles for the OH(vu = 7, 8, 9; ∆v = 2) emission (at 2.0 µm) is approximately 2.8 km, very similar to the theoretical model prediction by Liu and Swenson (2003). This agreement is an indication that these variations from the mean are likely caused by atmospheric tides and gravity waves

Adaptation Reduces Variability of the Neuronal Population Code

Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for general non-renewal processes to calculate the interval and count statistics of superimposed processes governed by a slow adaptation variable. For an ensemble of spike-frequency adapting neurons this results in the regularization of the population activity and an enhanced post-synaptic signal decoding. We confirm our theoretical results in a population of cortical neurons.Comment: 4 pages, 2 figure

Physical and mechanical properties of Oak (Quercus Persica) fruits

This research was conducted over one Iranian variety of Oak (Quercus Persica) with 70 observations. Physical and mechanical properties of oak are necessary for equipment used in activities such as transportation, storage, grading, packing etc. Properties which were measured include fruit dimensions, mass, volume, projected area, fruit density, geometric mean diameter, sphericity and surface area. Bulk density, porosity and also packing coefficient were measured. Experiments were carried out at Results showed that average mass and volume were 12.95 g and 10.27 mL, respectively. Dimensions increased from 41.85 to 61.09 mm in length, 14.45 to 25.02 mm in width and 14.42 to 24.38 mm in thickness. The mean projected area perpendicular to length, width and thickness obtained 433.91, 1085.48 and 1115.46 mm2, respectively. The geometric mean diameter and surface area were calculated as 27.638 mm and 2423.82 mm2, respectively, while sphericity was measured 51.78%. Elasticity modulus (E), maximum force which fruit can support (Fmax) and work which performed to this force have been determined