A Multi-modal Brain Image Registration Framework for US-guided Neuronavigation Systems - Integrating MR and US for Minimally Invasive Neuroimaging

US-guided neuronavigation exploits the simplicity of use and minimal invasiveness of Ultrasound (US) imaging and the high tissue resolution and signal-to-noise ratio of Magnetic Resonance Imaging (MRI) to guide brain surgeries. More specifically, the intra-operative 3D US images are combined with pre-operative MR images to accurately localise the course of instruments in the operative field with minimal invasiveness. Multi-modal image registration of 3D US and MR images is an essential part of such system. In this paper, we present a complete software framework that enables the registration US and MR brain scans based on a multi resolution deformable transform, tackling elastic deformations (i.e. brain shifts) possibly occurring during the surgical procedure. The framework supports also simpler and faster registration techniques, based on rigid or affine transforms, and enables the interactive visualisation and rendering of the overlaid US and MRI volumes. The registration was experimentally validated on a public dataset of realistic brain phantom images, at different levels of artificially induced deformations

W2WNet: A two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality

Ideally, Convolutional Neural Networks (CNNs) should be trained with high quality images with minimum noise and correct ground truth labels. Nonetheless, in many real-world scenarios, such high quality is very hard to obtain, and datasets may be affected by any sort of image degradation and mislabelling issues. This negatively impacts the performance of standard CNNs, both during the training and the inference phase. To address this issue we propose Wise2WipedNet (W2WNet), a new two-module Convolutional Neural Network, where a Wise module exploits Bayesian inference to identify and discard spurious images during the training and a Wiped module takes care of the final classification, while broadcasting information on the prediction confidence at inference time. The goodness of our solution is demonstrated on a number of public benchmarks addressing different image classification tasks, as well as on a real-world case study on histological image analysis. Overall, our experiments demonstrate that W2WNet is able to identify image degradation and mislabelling issues both at training and at inference time, with positive impact on the final classification accuracy

Non-invasive assessment of hormonal fluctuations during pregnancy in guanacos (Lama guanicoe) and its application in a wild population

Fil: Marozzi, Antonela Alejandra. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina.Fil: Marozzi, Antonela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Fil: Cantarelli, Verónica I. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Cantarelli, Verónica I. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias de la Salud; Argentina.Fil: Panebianco, Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Fil: Gomez, F. M. Universidad Nacional del Comahue. Asentamiento Universitario San Martín de los Andes; Argentina.Fil: Ovejero, Ramiro. Universidad Nacional de Tucumán; Argentina.Fil: Ovejero, Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Gregorio, P. F. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina.Fil: Gregorio, P. F. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Fil: Peña, F. Consejo Nacional de Investigaciones Científicas y Técnicas. Witral - Red de Investigaciones en conservación y manejo de vida silvestre en sistemas socio-ecológicos, Instituto Argentino de Investigaciones de Zonas Áridas; Argentina.Fil: Ponzio, Marina F. Universidad Nacional del Comahue. Asentamiento Universitario San Martín de los Andes; Argentina.Fil: Carmanchahi, Pablo Daniel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina.Fil: Carmanchahi, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Obtaining endocrinological profiles using non-invasive methodologies by the measurement of hormone fecal metabolites is a widely used method to monitor ovarian activity and pregnancy in wild species. These tools allow the obtention of physiological information without causing capture-related stress on the individuals. In this research, we aimed to 1) biologically validate a non-invasive method to assess fecal progestagens and estrogens fluctuations during gestation in guanacos (Lama guanicoe) and 2) apply this technique to assess pregnancy in a wild free-ranging population. Fecal samples were collected through the gestation period (∼12 months) of female guanacos in a 6.5-ha paddock. An increase in fecal metabolites of both hormones was detected. Progestagens increased gradually, in contrast to estrogens, which remained at basal values for most of the gestation period and peaked only a few days before calving. To assess pregnancy in wild free-ranging animals, fecal samples were collected from a population of La Payunia provincial reserve (Mendoza, Argentina) during the beginning of gestation and at the end of gestation. Through the first months of possible gestation, pregnant females represented between 40 and 80% of the population; at the end of gestation, only 20–40% of the females had confirmed pregnancies. Our results demonstrated that the polyclonal antisera and sexual hormone metabolite assays used here detect variations in the metabolites excreted through feces in guanacos and provide the possibility of non-invasive hormone monitoring of female reproductive status. Also, the findings in wild conditions suggest that natural abortions could have occurred during the first months of gestation. Although some abortions may be natural, the harsh environmental conditions that challenge the support of such a long gestational process may be another relevant factor to consider. The results obtained here enhance our understanding of the reproductive physiology of one of the most emblematic ungulates in South America.info:eu-repo/semantics/publishedVersionFil: Marozzi, Antonela Alejandra. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina.Fil: Marozzi, Antonela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Fil: Cantarelli, Verónica I. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Cantarelli, Verónica I. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias de la Salud; Argentina.Fil: Panebianco, Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Fil: Gomez, F. M. Universidad Nacional del Comahue. Asentamiento Universitario San Martín de los Andes; Argentina.Fil: Ovejero, Ramiro. Universidad Nacional de Tucumán; Argentina.Fil: Ovejero, Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Gregorio, P. F. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina.Fil: Gregorio, P. F. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina.Fil: Peña, F. Consejo Nacional de Investigaciones Científicas y Técnicas. Witral - Red de Investigaciones en conservación y manejo de vida silvestre en sistemas socio-ecológicos, Instituto Argentino de Investigaciones de Zonas Áridas; Argentina.Fil: Ponzio, Marina F. Universidad Nacional del Comahue. Asentamiento Universitario San Martín de los Andes; Argentina.Fil: Carmanchahi, Pablo Daniel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina.Fil: Carmanchahi, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Grupo de Investigaciones en Ecofisiología de Fauna Silvestre. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina

Colorectal Cancer Classification using Deep Convolutional Networks - An Experimental Study

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Higher locus coeruleus MRI contrast is associated with lower parasympathetic influence over heart rate variability

The locus coeruleus (LC) is a key node of the sympathetic nervous system and suppresses parasympathetic activity that would otherwise increase heart rate variability. In the current study, we examined whether LC-MRI contrast reflecting neuromelanin accumulation in the LC was associated with high-frequency heart rate variability (HF-HRV), a measure reflecting parasympathetic influences on the heart. Recent evidence indicates that neuromelanin, a byproduct of catecholamine metabolism, accumulates in the LC through young and mid adulthood, suggesting that LC-MRI contrast may be a useful biomarker of individual differences in habitual LC activation. We found that, across younger and older adults, greater LC-MRI contrast was negatively associated with HF-HRV during fear conditioning and spatial detection tasks. This correlation was not accounted for by individual differences in age or anxiety. These findings indicate that individual differences in LC structure relate to key cardiovascular parameters