Systematic segmentation method based on PCA of image hue features for white blood cell counting

Leukocyte (white blood cell, WBC) count is an essential factor that physicians use to diagnose infections and provide adequate treatment. Currently, WBC count is determined manually or semi-automatically, which often leads to miscounting. In this paper, we propose an automated method that uses a bioinspired segmentation mimicking the human perception of color. It is based on the claim that a person can locate WBCs in a blood smear image via the high chromatic contrast. First, by applying principal component analysis over RGB, HSV, and L*a*b* spaces, with specific combinations, pixels of leukocytes present high chromatic variance; this results in increased contrast with the average hue of the other blood smear elements. Second, chromaticity is processed as a feature, without separating hue components; this is different to most of the current automation that perform mathematical operations between hue components in an intuitive way. As a result of this systematic method, WBC recognition is computationally efficient, overlapping WBCs are separated, and the final count is more precise. In experiments with the ALL-IDB benchmark, the performance of the proposed segmentation was assessed by comparing the WBC from the processed images with the ground truth. Compared with previous methods, the proposed method achieved similar results in sensitivity and precision and approximately 0.2% higher specificity and 0.3% higher accuracy for pixel classification in the segmentation stage; as well, the counting results are similar to previous works.

Synergy of color and motion vision for detecting approaching objects in Drosophila

Color and motion are used by many species to identify salient moving objects. They are processed largely independently, but color contributes to motion processing in humans, for example, enabling moving colored objects to be detected when their luminance matches the background. Here, we demonstrate an unexpected, additional contribution of color to motion vision in Drosophila. We show that behavioral ON-motion responses are more sensitive to UV than for OFF-motion, and we identify cellular pathways connecting UV-sensitive R7 photoreceptors to ON and OFF-motion-sensitive T4 and T5 cells, using neurogenetics and calcium imaging. Remarkably, the synergy of color and motion vision enhances the detection of approaching UV discs, but not green discs with the same chromatic contrast, and we show how this generalizes for visual systems with ON and OFF pathways. Our results provide a computational and circuit basis for how color enhances motion vision to favor the detection of saliently colored objects.

Modeling chromatic contrast sensitivity across different background colors and luminance

In this research we compare chromatic contrast sensitivity models for two separate datasets and for the pooled dataset. They were obtained from two studies employing a very similar experimental paradigm. The data represent threshold visibilities of chromatic Gabor patterns varying in spatial frequency, background chromaticity, direction of color modulation and luminance, at constant stimulus size. Using the extended data set, we reconfirm our previously reported finding that a model based on coloropponent contrast signals is an improvement over a cone contrast model. However, when linear background scaling in classic cone contrast is replaced by nonlinear background scaling, an improvement of almost similar size is obtained. The results of this study can be of interest for the development of vision models employing the processing of spatio-chromatic information.

Major Flower Pigments Originate Different Colour Signals to Pollinators

Flower colour is mainly due to the presence and type of pigments. Pollinator preferences impose selection on flower colour that ultimately acts on flower pigments. Knowing how pollinators perceive flowers with different pigments becomes crucial for a comprehensive understanding of plant-pollinator communication and flower colour evolution. Based on colour space models, we studied whether main groups of pollinators, specifically hymenopterans, dipterans, lepidopterans and birds, differentially perceive flower colours generated by major pigment groups. We obtain reflectance data and conspicuousness to pollinators of flowers containing one of the pigment groups more frequent in flowers: chlorophylls, carotenoids and flavonoids. Flavonoids were subsequently classified in UV-absorbing flavonoids, aurones-chalcones and the anthocyanins cyanidin, pelargonidin, delphinidin, and malvidin derivatives. We found that flower colour loci of chlorophylls, carotenoids, UV-absorbing flavonoids, aurones-chalcones, and anthocyanins occupied different regions of the colour space models of these pollinators. The four groups of anthocyanins produced a unique cluster of colour loci. Interestingly, differences in colour conspicuousness among the pigment groups were almost similar in the bee, fly, butterfly, and bird visual space models. Aurones-chalcones showed the highest chromatic contrast values, carotenoids displayed intermediate values, and chlorophylls, UV-absorbing flavonoids and anthocyanins presented the lowest values. In the visual model of bees, flowers with UV-absorbing flavonoids (i.e., white flowers) generated the highest achromatic contrasts. Ours findings suggest that in spite of the almost omnipresence of floral anthocyanins in angiosperms, carotenoids and aurones-chalcones generates higher colour conspicuousness for main functional groups of pollinators.

In a Neotropical Periurban Park, Fruit Consumption by Birds Seems to Be a Random Process

Frugivory interactions between birds and fruit-bearing plants are shaped by the abundance of its interacting species, their temporal overlap, the matching of their morphologies, as well as fruit and seed characteristics. Our study evaluates the role of seven factors of fruits and plants in determining the frequency of whole-fruit consumption by birds. We studied the frugivory network of a Neotropical periurban park in Xalapa, Veracruz, Mexico, and quantified relative abundance and phenology of birds and fruit, as well as fruit morphology, chromatic and achromatic contrast, and nutritional content. Using a maximum likelihood approach, we compared the observed interaction network with 62 single- and multiple-variable probabilistic models. Our network is composed of 11 plants and 17 birds involved in 81 frugivory interactions. This network is nested, modular, and relatively specialized. However, the frequency of pairwise interactions is not explained by the variables examined in our probabilistic models and found the null model has the best performance. This indicates that no single predictor or combination of them is better at explaining the observed frequency of pairwise interactions than the null model. The subsequent four top-ranking models, with ΔAIC values < 100, are single-variable ones: carbohydrate content, lipid content, chromatic contrast, and morphology. Two- and three-variable models show the poorest fit to observed data. The lack of a deterministic pattern does not support any of our predictions nor neutral- or niche-based processes shaping the observed pattern of fruit consumption in our interaction network. It may also mean that fruit consumption by birds in this periurban park is a random process. Although our study failed to find a pattern, our work exemplifies how investigations done in urban settings, poor in species and interactions, can help us understand the role of disturbance in the organization of frugivory networks and the processes governing their structure.

The visual ecology of selective predation: Are unhealthy hosts less stealthy hosts?

Predators can strongly influence disease transmission and evolution, particularly when they prey selectively on infected hosts. Although selective predation has been observed in numerous systems, why predators select infected prey remains poorly understood. Here, we use a model of predator vision to test a longstanding hypothesis as to the mechanistic basis of selective predation in a Daphnia-microparasite system, which serves as a model for the ecology and evolution of infectious diseases. Bluegill sunfish feed selectively on Daphnia with a variety of parasites, particularly in water uncolored by dissolved organic carbon. The leading hypothesis for selective predation in this system is that infection-induced changes in the appearance of Daphnia render them more visible to bluegill. Rigorously evaluating this hypothesis requires that we quantify the effect of infection on the visibility of prey from the predator’s perspective, rather than our own. Using a model of the bluegill visual system, we show that the three common parasites, Metschnikowia bicuspidata, Pasteuria ramosa and Spirobacillus cienkowskii, increase the opacity of Daphnia, rendering infected Daphnia darker against the background of downwelling light. As a result of this increased brightness contrast, bluegill can see infected Daphnia at greater distances than uninfected Daphnia – between 19-33% further, depending on the parasite. Pasteuria and Spirobacillus also increase the chromatic contrast of Daphnia. Contrary to expectations, the visibility Daphnia was not strongly impacted by water color in our model. Our work generates hypotheses about which parasites are most likely affected by selective predation in this important model system and establishes visual models as a valuable tool for understanding ecological interactions that impact disease transmission.

The influence of temporal frequency and stimulus size on the relative contribution of luminance and L-/M-cone opponent mechanisms in heterochromatic flicker ERGs

Purpose To study the effect of stimulus size and temporal frequency on the relative contribution of luminance and L-/M-cone opponent signals in the ERG. Methods In four healthy, color normal subjects, ERG responses to heterochromatic stimuli with sinusoidal, counter-phase modulation of red and green LEDs were measured. By inverse variation of red and green contrasts, we varied luminance contrast while keeping L-/M-cone opponent chromatic contrast constant. The first harmonic components in the full field ERGs are independent of stimulus contrast at 12 Hz, while responses to 36 Hz stimuli vary, reaching a minimum close to isoluminance. It was assumed that ERG responses reflect L-/M-cone opponency at 12 Hz and luminance at 36 Hz. In this study, we modeled the influence of temporal frequency on the relative contribution of these mechanisms at intermediate frequencies, measured the influence of stimulus size on model parameters, and analyzed the second harmonic component at 12 Hz. Results The responses at all frequencies and stimulus sizes could be described by a linear vector addition of luminance and L-/M-cone opponent reflecting ERGs. The contribution of the luminance mechanism increased with increasing temporal frequency and with increasing stimulus size, whereas the gain of the L-/M-cone opponent mechanism was independent of stimulus size and was larger at lower temporal frequencies. Thus, the luminance mechanism dominated at lower temporal frequencies with large stimuli. At 12 Hz, the second harmonic component reflected the luminance mechanism. Conclusions The ERGs to heterochromatic stimuli can be fully described in terms of linear combinations of responses in the (magnocellular) luminance and the (parvocellular) L-/M-opponent retino-geniculate pathways. The non-invasive study of these pathways in human subjects may have implications for basic research and for clinical research.

Temporal filtering of luminance and chromaticity in macaque visual cortex

The visibility of a periodic light modulation depends on its temporal frequency and spectral properties. Contrast sensitivity is highest at 8 to 10 Hz for modulations of luminance but is substantially lower for modulations between equiluminant lights. This difference between luminance and chromatic contrast sensitivity is rooted in retinal filtering, but additional filtering occurs in the cerebral cortex. To measure the cortical contributions to luminance and chromatic temporal contrast sensitivity, signals in the lateral geniculate nucleus (LGN) were compared to the behavioral contrast sensitivity of macaque monkeys. Long wavelength-sensitive (L) and medium wavelength-sensitive (M) cones were modulated in phase, to produce a luminance modulation (L+M), or in counterphase, to produce a chromatic modulation (L-M). The sensitivity of LGN neurons was well matched to behavioral sensitivity at low temporal frequencies but was approximately 7 times greater at high temporal frequencies. Similar results were obtained for L+M and L-M modulations. These results show that differences in the shapes of the luminance and chromatic temporal contrast sensitivity functions are due almost entirely to pre-cortical mechanisms. Simulations of cone photoreceptor currents show that temporal information loss in the retina and at the retinogeniculate synapse exceeds cortical information loss under most of the conditions tested.

Polarization contrasts and their effect on the gaze stabilisation of crustaceans

Many animals go to great lengths to stabilise their eyes relative to the visual scene and do so to enhance the localisation of moving objects and to functionally partition the visual system relative to the outside world. An important cue that is used to control these stabilisation movements is contrast within the visual surround. Previous studies on insects, spiders and fish have shown that gaze stabilisation is achromatic (= ‘colour-blind’), meaning that chromatic contrast alone (in the absence of apparent intensity contrasts) does not contribute to gaze stabilisation. Following the assumption that polarization vision is analogous in many ways to colour vision, the present study shows that five different crustacean species do not use the polarization of light alone for gaze stabilisation, despite being able to use this modality for detecting predator-like objects. This work therefore suggests that the gaze stabilisation in many crustaceans cannot be elicited by the polarization of light alone.