Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast

Partial voluming (PV) is arguably the last crucial unsolved problem in Bayesian segmentation of brain MRI with probabilistic atlases. PV occurs when voxels contain multiple tissue classes, giving rise to image intensities that may not be representative of any one of the underlying classes. PV is particularly problematic for segmentation when there is a large resolution gap between the atlas and the test scan, e.g., when segmenting clinical scans with thick slices, or when using a high-resolution atlas. In this work, we present PV-SynthSeg, a convolutional neural network (CNN) that tackles this problem by directly learning a mapping between (possibly multi-modal) low resolution (LR) scans and underlying high resolution (HR) segmentations. PV-SynthSeg simulates LR images from HR label maps with a generative model of PV, and can be trained to segment scans of any desired target contrast and resolution, even for previously unseen modalities where neither images nor segmentations are available at training. PV-SynthSeg does not require any preprocessing, and runs in seconds. We demonstrate the accuracy and flexibility of the method with extensive experiments on three datasets and 2,680 scans. The code is available at https://github.com/BBillot/SynthSeg.Comment: accepted for MICCAI 202

Organic residues in archaeology - the highs and lows of recent research

YesThe analysis of organic residues from archaeological materials has become increasingly important to our understanding of ancient diet, trade and technology. Residues from diverse contexts have been retrieved and analysed from the remains of food, medicine and cosmetics to hafting material on stone arrowheads, pitch and tar from shipwrecks, and ancient manure from soils. Research has brought many advances in our understanding of archaeological, organic residues over the past two decades. Some have enabled very specific and detailed interpretations of materials preserved in the archaeological record. However there are still areas where we know very little, like the mechanisms at work during the formation and preservation of residues, and areas where each advance produces more questions rather than answers, as in the identification of degraded fats. This chapter will discuss some of the significant achievements in the field over the past decade and the ongoing challenges for research in this area.Full text was made available in the Repository on 15th Oct 2015, at the end of the publisher's embargo period

Integrated Multi-Parameter Exploration Footprints of the Canadian Malartic Disseminated Au, McArthur River-Millennium Unconformity U, and Highland Valley Porphyry Cu Deposits: Preliminary Results from the NSERC-CMIC Mineral Exploration Footprints Research Network

Mineral exploration in Canada is increasingly focused on concealed and deeply buried targets, requiring more effective tools to detect large-scale ore-forming systems and to vector from their most distal margins to their high grade cores. A new generation of ore system models is required to achieve this. The Mineral Exploration Footprints Research Network is a consortium of 70 faculty, research associates, and students from 20 Canadian universities working with 30 mining, mineral exploration, and mining service providers to develop new approaches to ore system modelling based on more effective integration and visualization of multi-parameter geological-structural-mineralogical-lithogeochemical-petrophysical-geophysical exploration data. The Network is developing the next generation ore system models and exploration strategies at three sites based on integrated data visualization using self-consistent 3D Common Earth Models and geostatistical/machine learning technologies. Thus far over 60 footprint components and vectors have been identified at the Canadian Malartic stockwork-disseminated Au deposit, 20–30 at the McArthur-Millennium unconformity U deposits, and over 20 in the Highland Valley porphyry Cu system. For the first time, these are being assembled into comprehensive models that will serve as landmark case studies for data integration and analysis in the today’s challenging exploration environment

Sophorolipid biosurfactants: Possible uses as antibacterial and antibiofilm agent

Biosurfactants are amphipathic, surface-active molecules of microbial origin which accumulate at interfaces reducing interfacial tension and leading to the formation of aggregated micellular structures in solution. Some biosurfactants have been reported to have antimicrobial properties, the ability to prevent adhesion and to disrupt biofilm formation. We investigated antimicrobial properties and biofilm disruption using sophorolipids at different concentrations. Growth of Gram negative Cupriavidus necator ATCC 17699 and Gram positive Bacillus subtilis BBK006 were inhibited by sophorolipids at concentrations of 5% v/v with a bactericidal effect. Sophorolipids (5% v/v) were also able to disrupt biofilms formed by single and mixed cultures of B. subtilis BBK006 and Staphylococcus aureus ATCC 9144 under static and flow conditions, as was observed by scanning electron microscopy. The results indicated that sophorolipids may be promising compounds for use in biomedical application as adjuvants to other antimicrobial against some pathogens through inhibition of growth and/or biofilm disruption