Discover the most talked about and latest scientific content & concepts.

Concept: Segmentation


Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of “smart markers” for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

Concepts: Better, Microscope, Microscopy, Numerical analysis, Image processing, Phase-contrast imaging, Watershed, Segmentation


With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on the detection accuracy, has not been addressed properly. In this context, this work develops a calibration strip for ICG assay photoelectric detection systems. An image of the test strip is captured by an image acquisition device, followed by performing a fuzzy c-means (FCM) clustering algorithm and maximin-distance algorithm for image segmentation. Additionally, experiments are conducted to find the best characteristic quantity. By analyzing the linear coefficient, an average value of hue (H) at 14 min is chosen as the characteristic quantity and the empirical formula between H and optical density (OD) value is established. Therefore, H, saturation (S), and value (V) are calculated by a number of selected OD values. Then, H, S, and V values are transferred to the RGB color space and a high-resolution printer is used to print the strip images on cellulose nitrate membranes. Finally, verification of the printed calibration strips is conducted by analyzing the linear correlation between OD and the spectral reflectance, which shows a good linear correlation (R² = 98.78%).

Concepts: Cluster analysis, Function, Color, RGB color model, Color space, Segmentation, RGB color space, Adobe RGB color space


The accuracy of additive manufactured medical constructs is limited by errors introduced during image segmentation. The aim of this study was to review the existing literature on different image segmentation methods used in medical additive manufacturing.

Concepts: Manufacturing, Rapid manufacturing, Segmentation


: The purpose of this study was to analyze the transference of increased passive hip ROM and core endurance to functional movement. 24 healthy young men with limited hip mobility were randomly assigned to 4 intervention groups: 1)Stretching; 2)Stretching plus hip/spine disassociation exercises; 3)Core endurance; 4)Control. Previous work has documented the large increase in passive ROM and core endurance that was attained over the 6 week interventions, but whether these changes transferred to functional activities was unclear.Four dynamic activities were analyzed before and after the 6 week interventions: active standing hip extension, lunge, a standing twist/reach maneuver, and exercising on an elliptical trainer. A Vicon motion capture system collected body segment kinematics, with hip and lumbar spine angles subsequently calculated in Visual 3D. Repeated measures ANOVAs determined group effects on various hip and spine angles, with paired t-tests on specific pre/post pairs.Despite the large increases in passive hip ROM, there was no evidence of increased hip ROM utilized during functional movement testing. Similarly, the only significant change in lumbar motion was a reduction in lumbar rotation during the active hip extension manoeuvre (p< 0.05).These results indicate that changes in passive ROM or core endurance do not automatically transfer to changes in functional movement patterns. This implies that training and rehabilitation programs may benefit from an additional focus on 'grooving' new motor patterns if new found movement range is to be utilized.

Concepts: Lumbar vertebrae, Physical exercise, Intervention, Motion capture, Active, Segmentation, Core, Elliptical trainer


During embryonic development, temporal and spatial cues are coordinated to generate a segmented body axis. In sequentially segmenting animals, the rhythm of segmentation is reported to be controlled by the time scale of genetic oscillations that periodically trigger new segment formation. However, we present real-time measurements of genetic oscillations in zebrafish embryos showing that their time scale is not sufficient to explain the temporal period of segmentation. A second time scale, the rate of tissue shortening, contributes to the period of segmentation through a Doppler effect. This contribution is modulated by a gradual change in the oscillation profile across the tissue. We conclude that the rhythm of segmentation is an emergent property controlled by the time scale of genetic oscillations, the change of oscillation profile, and tissue shortening.

Concepts: Time, Embryo, Developmental biology, Oscillation, Wave, Doppler effect, Periodic function, Segmentation


We aim to improve segmentation through the use of machine learning tools during region agglomeration. We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple features at all scales of the agglomerative process, works for data with an arbitrary number of dimensions, and scales to very large datasets. We advocate the use of variation of information to measure segmentation accuracy, particularly in 3D electron microscopy (EM) images of neural tissue, and using this metric demonstrate an improvement over competing algorithms in EM and natural images.

Concepts: Cluster analysis, Algorithm, Improve, Computer graphics, Machine learning, Real number, Scanning tunneling microscope, Segmentation


The diverse and complex developmental mechanisms of segmentation have been more thoroughly studied in arthropods, vertebrates and annelids-distantly related animals considered to be segmented. Far less is known about the role of “segmentation genes” in organisms that lack a segmented body. Here we investigate the expression of the arthropod segment polarity genes engrailed, wnt1 and hedgehog in the development of brachiopods-marine invertebrates without a subdivided trunk but closely related to the segmented annelids. We found that a stripe of engrailed expression demarcates the ectodermal boundary that delimits the anterior region of Terebratalia transversa and Novocrania anomala embryos. In T. transversa, this engrailed domain is abutted by a stripe of wnt1 expression in a pattern similar to the parasegment boundaries of insects-except for the expression of hedgehog, which is restricted to endodermal tissues of the brachiopod embryos. We found that pax6 and pax2/5/8, putative regulators of engrailed, also demarcate the anterior boundary in the two species, indicating these genes might be involved in the anterior patterning of brachiopod larvae. In a comparative phylogenetic context, these findings suggest that bilaterians might share an ancestral, non-segmental domain of engrailed expression during early embryogenesis.

Concepts: Organism, Species, Developmental biology, Arthropod, Annelid, Segmentation, Brachiopod, Modularity


To what extent can language acquisition be explained in terms of different associative learning mechanisms? It has been hypothesized that distributional regularities in spoken languages are strong enough to elicit statistical learning about dependencies among speech units. Distributional regularities could be a useful cue for word learning even without rich language-specific knowledge. However, it is not clear how strong and reliable the distributional cues are that humans might use to segment speech. We investigate cross-linguistic viability of different statistical learning strategies by analyzing child-directed speech corpora from nine languages and by modeling possible statistics-based speech segmentations. We show that languages vary as to which statistical segmentation strategies are most successful. The variability of the results can be partially explained by systematic differences between languages, such as rhythmical differences. The results confirm previous findings that different statistical learning strategies are successful in different languages and suggest that infants may have to primarily rely on non-statistical cues when they begin their process of speech segmentation.

Concepts: Scientific method, Linguistics, Language, Machine learning, Learning, Knowledge, Universal grammar, Segmentation


For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems. Thus, it is useful to evaluate the ability of simple methods to segment images with various degrees of crowded nuclei.

Concepts: Developmental biology, Caenorhabditis elegans, Caenorhabditis, Rhabditidae, Caenorhabditis briggsae, Segmentation


Labile surfaces in the form of suspension straps are increasingly being utilized as a tool in resistance training programs. Pushing is a common functional activity of daily living and inherently part of a well-rounded training program. This study examined pushing exercises performed on stable surfaces and unstable suspension straps, specifically muscle activation levels and spine loads were quantified together with the influence of employing technique coaching.There were several main questions that this study sought to answer: which exercises challenged particular muscles, what was the magnitude of the resulting spine load, how did stable and unstable surfaces differ and did coaching influence the results.Fourteen males were recruited as part of a convenience sample (mean age of 21.1 ± 2.0 years, 1.77 ± 0.06 m in height and a mean weight of 74.6 ± 7.8 kg). Data was processed and input to a sophisticated and anatomically detailed 3D model that used muscle activity and body segment kinematics to estimate muscle force - in this way the model was sensitive to the individuals choice of motor control for each task; muscle forces and linked segment joint loads were used to calculate spine loads. Exercises were performed using stable surfaces for hand/feet contact and repeated where possible with labile suspension straps. Speed of movement was standardized across participants with the use of a metronome for each exercise.There were gradations of muscle activity and spine load characteristics to every task. In general, the instability associated with the labile exercises required greater torso muscle activity than when performed on stable surfaces. Throughout the duration of an exercise there was a range of compression; the TRX Pushup ranged from 1653 N to 2128.14 N while the Standard Pushup had a range from 1233.75 N to 1530.06 N. There was no significant effect of exercise on spine compression (F(4,60)=0.86, p=0.495). Interestingly a standard pushup showed significantly greater shear than TRX angle 1 (p=0.02), angle 2 (p=0.01) and angle 3 (p=0.02).As with any training program for the elite or recreational athlete alike, specific exercises and programs should reflect ones injury history, capabilities, limitations and training goals. Although none of the exercises examined here breached the NIOSH action limit for compression, those exercises that produced higher loads should be used relative to the individual. Thus the atlas of muscle activation, compression and shear forces provided can be used to create an appropriate program. Those individuals not able to tolerate certain loads may refer to the atlas and choose exercises that minimize load and still provide sufficient muscle activation. Conversely an individual with a resilient back that requires an increased muscular challenge may choose exercises with higher muscle activation and spine load. This helps the individual, trainer or coach in program design respecting individual differences and training goals.

Concepts: Muscle, Physical exercise, Exercise, Muscular system, Strength training, Weight training, Shear stress, Segmentation