Carlos A. Silva

Bio: Carlos A. Silva is an academic researcher from University of Florida. The author has contributed to research in topics: ISTTOK & Tokamak. The author has an hindex of 55, co-authored 765 publications receiving 17298 citations. Previous affiliations of Carlos A. Silva include Goddard Space Flight Center & Universidade Federal de Santa Catarina.

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

Abstract: In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients—manually annotated by up to four raters—and to 65 comparable scans generated using tumor image simulation software Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%–85%), illustrating the difficulty of this task We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Abstract: Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 $\times$ 3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

Informing network users of television programming viewed by other network users

Abstract: A method of informing a first network user of activity by other network users includes receiving information identifying television programming viewed by at least one other network user and displaying the information to the first network user on a user interface.

The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography

Abstract: Obtaining accurate and widespread measurements of the vertical structure of the Earth’s forests has been a long-sought goal for the ecological community. Such observations are critical for accurately assessing the existing biomass of forests, and how changes in this biomass caused by human activities or variations in climate may impact atmospheric CO2 concentrations. Additionally, the three-dimensional structure of forests is a key component of habitat quality and biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6° N & S latitude. The GEDI instrument is a geodetic-class laser altimeter/waveform lidar comprised of 3 lasers that produce 8 transects of structural information. Over its two-year nominal lifetime GEDI is anticipated to provide over 10 billion waveforms at a footprint resolution of 25 ​m. These data will be used to derive a variety of footprint and gridded products, including canopy height, canopy foliar profiles, Leaf Area Index (LAI), sub-canopy topography and biomass. Additionally, data from GEDI are used to demonstrate the efficacy of its measurements for prognostic ecosystem modeling, habit and biodiversity studies, and for fusion using radar and other remote sensing instruments. GEDI science and technology are unique: no other space-based mission has been created that is specifically optimized for retrieving vegetation vertical structure. As such, GEDI promises to advance our understanding of the importance of canopy vertical variations within an ecological paradigm based on structure, composition and function.

Evidence for middle Eocene and younger land emergence in central Panama: Implications for Isthmus closure

Abstract: The rise of the Isthmus of Panama, linked to a number of climatic, paleoceanographic, and biological events, has been studied mostly from indirect, often distal, geochemical and biotic evidence. We have upgraded existing geologic mapping in central Panama with more than 2000 field stations, over 40 petrographic analyses, and more than 30 new geochronological and thermochronological analyses. This data set suggests that the isthmus was an uninterrupted chain above sea level from late Eocene until at least late Miocene times. The basement complex of central Panama is a folded-faulted, ∼3-km-thick arc sequence, intruded by granitoid bodies and onlapped by mildly deformed upper Eocene and Oligocene strata. Six U/Pb zircon ages in the granitoids–along with published geochronological data—reveal intense late Paleocene to middle Eocene magmatism (58–39 Ma), a temporary cessation of magmatic activity between 38 and 27 Ma, and renewed magmatism between 25 and 15 Ma in a position ∼75 km south of the former magmatic axis. Thermochronological analyses in zircon (eight U-Th/He ages), and in apatite crystals (four U-Th/He ages and nine fission-track ages) obtained from a subset of 58–54 Ma granitoid bodies record a concordant Lutetian-age (47–42 Ma) cooling from ∼200 °C to ∼70 °C in ∼5 m.y., and cooling below ∼40 °C between 12 and 9 Ma. Cooling is linked to exhumation by an angular unconformity that separates the deformed basement complex below from mildly deformed, upper Eocene to Oligocene terrestrial to shallow-marine strata above. Exhumation and erosion of the basement complex are independently confirmed by lower Miocene strata that have a detrital zircon signature that closely follows the central Panama basement complex age distribution. These results greatly restrict the width and depth of the strait separating southern Central America from South America, and challenge the widely accepted notion that the Central American Seaway closed in late Pliocene time, when the ice age began.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Modern Applied Statistics With S

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