Signaling local non-credibility in an automatic segmentation pipeline

The advancing technology for automatic segmentation of medical images should be accompanied by techniques to inform the user of the local credibility of results. To the extent that this technology produces clinically acceptable segmentations for a significant fraction of cases, there is a risk that the clinician will assume every result is acceptable. In the less frequent case where segmentation fails, we are concerned that unless the user is alerted by the computer, she would still put the result to clinical use. By alerting the user to the location of a likely segmentation failure, we allow her to apply limited validation and editing resources where they are most needed. We propose an automated method to signal suspected non-credible regions of the segmentation, triggered by statistical outliers of the local image match function. We apply this test to m-rep segmentations of the bladder and prostate in CT images using a local image match computed by PCA on regional intensity quantile functions. We validate these results by correlating the non-credible regions with regions that have surface distance greater than 5.5mm to a reference segmentation for the bladder. A 6mm surface distance was used to validate the prostate results. Varying the outlier threshold level produced a receiver operating characteristic with area under the curve of 0.89 for the bladder and 0.92 for the prostate. Based on this preliminary result, our method has been able to predict local segmentation failures and shows potential for validation in an automatic segmentation pipeline

An antiemetic for irritable bowel syndrome?

An antiemetic for irritable bowel syndrome? A drug used for cancer patients may provide some relief to patients with IBS. Practice changer: Consider prescribing ondansetron up to 24 mg/d for patients who have irritable bowel syndrome with diarrhea (IBS-D)

Atmospheric Chemistry Over Southern Africa

During the southern African dry season, regional haze from mixed industrial pollution, biomass burning aerosol and gases from domestic and grassland fires, and biogenic sources from plants and soils is worsened by a semi-permanent atmosphere gyre over the subcontinent. These factors were a driver of several major international field campaigns in the 1990s and early 2000s, and attracted many scientists to the region. Some researchers were interested in understanding fundamental processes governing chemistry of the atmosphere and interaction with climate change. Others found favorable conditions for evaluating satellite-derived measurements of atmospheric properties and a changing land surface. With that background in mind a workshop on atmospheric chemistry was held in South Africa. Sponsored by the International Commission for Atmospheric Chemistry and Global Pollution (ICACGP; http://www.icacgp.org/), the workshop received generous support from the South African power utility, Eskom, and the Climatology Research Group of the University of the Witwatersrand, Johannesburg, South Africa. The purpose of the workshop was to review some earlier findings as well as more recent findings on southern African climate vulnerability, chemical changes due to urbanization, land-use modification, and how these factors interact. Originally proposed by John Burrows, president of ICACGP, the workshop was the first ICACGP regional workshop to study the interaction of air pollution with global chemical and climate change. Organized locally by the University of the Witwatersrand, the workshop attracted more than 60 delegates from South Africa, Mozambique, Botswana, Zimbabwe, France, Germany, Canada, and the United States. More than 30 presentations were given, exploring both retrospective and prospective aspects of the science. In several talks, attention was focused on southern African chemistry, atmospheric pollution monitoring, and climate processes as they were studied in the field campaigns such as Transport and Atmospheric Chemistry Near the Equator-Atlantic (TRACE-A), Southern African Fire-Atmosphere Research Initiative (SAFARI-92), and Southern African Regional Science Initiative (SAFARI 2000). Since those large international efforts, satellites have matured enough to enable quantifiable measurements of regional land surface, atmosphere, and ocean. In addition, global and chemical transport models have also been advanced to incorporate various data. Thus, the timing of the workshop was right for a full-fledged re-assessment of the chemistry, physics, and socio-economical impacts caused by pollution in the region, including a characterization of sources, deposition, and feedbacks with climate change

KK-theoretic counterexamples to Ravenel's telescope conjecture

At each prime $p$ and height $n+1 \ge 2$, we prove that the telescopic and chromatic localizations of spectra differ. Specifically, for $\mathbb{Z}$ acting by Adams operations on $\mathrm{BP}\langle n \rangle$, we prove that the $T(n+1)$-localized algebraic $K$-theory of $\mathrm{BP}\langle n \rangle^{h\mathbb{Z}}$ is not $K(n+1)$-local. We also show that Galois hyperdescent, $\mathbb{A}^1$-invariance, and nil-invariance fail for the $K(n+1)$-localized algebraic $K$-theory of $K(n)$-local $\mathbb{E}_{\infty}$-rings. In the case $n=1$ and $p \ge 7$ we make complete computations of $T(2)_*\mathrm{K}(R)$, for $R$ certain finite Galois extensions of the $K(1)$-local sphere. We show for $p\geq 5$ that the algebraic $K$-theory of the $K(1)$-local sphere is asymptotically $L_2^{f}$-local.Comment: 100 pages. Comments very welcom

Dysembryoplastic neuroepithelial tumor with atypical presentation: MRI and diffusion tensorcharacteristics

We report the neuroimaging findings of a 26-year-old female patient with a biopsy-proven dysembryoplastic neuroepithelial tumor (DNET). DNETs are an uncommon, usually benign, glial-neural cortical neoplasm of children and young adults who typically present with intractable seizures. DNETs may occur in any region of the supratentorial cortex, but have a predilection for the temporal lobes. Accurate neuroimaging diagnosis is essential since patients with DNET benefit from complete resection. However, accurate differentiation from other cortical lesions may be challenging. Typical conventional Magnetic Resonance Imaging (MRI) features can help in the differentiation from other similar cortical tumors. Diffusion tensor imaging can also provide important additional diagnostic information regarding the degree of involvement of adjacent parenchyma and white matter tracts. In this case, tractography and fractional anisotropy maps demonstrated that fiber tracts surrounding the lesion were displaced, but fiber integrity was maintained, which is more suggestive of a DNET rather than a more aggressive neoplasm. Accurate identification of DNETs is essential for the purpose of rendering a timely diagnosis and start appropriate treatment

Implications of Electronics Constraints for Solid-State Quantum Error Correction and Quantum Circuit Failure Probability

In this paper we present the impact of classical electronics constraints on a solid-state quantum dot logical qubit architecture. Constraints due to routing density, bandwidth allocation, signal timing, and thermally aware placement of classical supporting electronics significantly affect the quantum error correction circuit's error rate. We analyze one level of a quantum error correction circuit using nine data qubits in a Bacon-Shor code configured as a quantum memory. A hypothetical silicon double quantum dot quantum bit (qubit) is used as the fundamental element. A pessimistic estimate of the error probability of the quantum circuit is calculated using the total number of gates and idle time using a provably optimal schedule for the circuit operations obtained with an integer program methodology. The micro-architecture analysis provides insight about the different ways the electronics impact the circuit performance (e.g., extra idle time in the schedule), which can significantly limit the ultimate performance of any quantum circuit and therefore is a critical foundation for any future larger scale architecture analysis.Comment: 10 pages, 7 figures, 3 table

Exploring Aerosols near Clouds with High-Spatial-Resolution Aircraft Remote Sensing During SEAC4RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satelliteborne Moderateresolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 m) in cloudfree scenes. Since MODIS' resolution (500m pixels, 3 or 10km product) is too coarse for studying nearcloud aerosol, we ported the Dark Target algorithm to the highresolution (~50m pixels) enhancedMODIS Airborne Simulator (eMAS), which flew on the highaltitude ER2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degradedresolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and groundbased Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into nearcloud and farfromcloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clearcloud transition zone microphysics such as aerosol swelling. However, 3D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds

Real-Time Decision Fusion for Multimodal Neural Prosthetic Devices

The field of neural prosthetics aims to develop prosthetic limbs with a brain-computer interface (BCI) through which neural activity is decoded into movements. A natural extension of current research is the incorporation of neural activity from multiple modalities to more accurately estimate the user's intent. The challenge remains how to appropriately combine this information in real-time for a neural prosthetic device., i.e., fusing predictions from several single-modality decoders to produce a more accurate device state estimate. We examine two algorithms for continuous variable decision fusion: the Kalman filter and artificial neural networks (ANNs). Using simulated cortical neural spike signals, we implemented several successful individual neural decoding algorithms, and tested the capabilities of each fusion method in the context of decoding 2-dimensional endpoint trajectories of a neural prosthetic arm. Extensively testing these methods on random trajectories, we find that on average both the Kalman filter and ANNs successfully fuse the individual decoder estimates to produce more accurate predictions.Our results reveal that a fusion-based approach has the potential to improve prediction accuracy over individual decoders of varying quality, and we hope that this work will encourage multimodal neural prosthetics experiments in the future

An Ultra-Thin Polymer Coating for the Tethering of Adenoviral Vector to the Surface of Coronary Stents

Our group has previously demonstrated stent-based gene delivery with either viral or plasmid vectors. However, these previous studies utilized bulky PLGA or collagen stent coatings, known to cause inflammatory reactions in stented arteries. In the present experiments we successfully attached adenoviruses either directly, or via anti-adenovirus antibodies to the steel surface of stents using chemical coordination with biphosphonates