Automatic assessment of time-resolved OCT images for selective retina therapy

Purpose In recent years, selective retina laser treatment (SRT), a sub-threshold therapy method, avoids widespread damage to all retinal layers by targeting only a few. While these methods facilitate faster healing, their lack of visual feedback during treatment represents a considerable shortcoming as induced lesions remain invisible with conventional imaging and make clinical use challenging. To overcome this, we present a new strategy to provide location-specific and contact-free automatic feedback of SRT laser applications. Methods We leverage time-resolved optical coherence tomography (OCT) to provide informative feedback to clinicians on outcomes of location-specific treatment. By coupling an OCT system to SRT treatment laser, we visualize structural changes in the retinal layers as they occur via time-resolved depth images. We then propose a novel strategy for automatic assessment of such time-resolved OCT images. To achieve this, we introduce novel image features for this task that when combined with standard machine learning classifiers yield excellent treatment outcome classification capabilities. Results Our approach was evaluated on both ex vivo porcine eyes and human patients in a clinical setting, yielding performances above 95 % accuracy for predicting patient treatment outcomes. In addition, we show that accurate outcomes for human patients can be estimated even when our method is trained using only ex vivo porcine data. Conclusion The proposed technique presents a much needed strategy toward noninvasive, safe, reliable, and repeatable SRT applications. These results are encouraging for the broader use of new treatment options for neovascularization-based retinal pathologies.

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.

Automatic quality control in clinical (1) H MRSI of brain cancer.

MRSI grids frequently show spectra with poor quality, mainly because of the high sensitivity of MRS to field inhomogeneities. These poor quality spectra are prone to quantification and/or interpretation errors that can have a significant impact on the clinical use of spectroscopic data. Therefore, quality control of the spectra should always precede their clinical use. When performed manually, quality assessment of MRSI spectra is not only a tedious and time-consuming task, but is also affected by human subjectivity. Consequently, automatic, fast and reliable methods for spectral quality assessment are of utmost interest. In this article, we present a new random forest-based method for automatic quality assessment of (1) H MRSI brain spectra, which uses a new set of MRS signal features. The random forest classifier was trained on spectra from 40 MRSI grids that were classified as acceptable or non-acceptable by two expert spectroscopists. To account for the effects of intra-rater reliability, each spectrum was rated for quality three times by each rater. The automatic method classified these spectra with an area under the curve (AUC) of 0.976. Furthermore, in the subset of spectra containing only the cases that were classified every time in the same way by the spectroscopists, an AUC of 0.998 was obtained. Feature importance for the classification was also evaluated. Frequency domain skewness and kurtosis, as well as time domain signal-to-noise ratios (SNRs) in the ranges 50-75 ms and 75-100 ms, were the most important features. Given that the method is able to assess a whole MRSI grid faster than a spectroscopist (approximately 3 s versus approximately 3 min), and without loss of accuracy (agreement between classifier trained with just one session and any of the other labelling sessions, 89.88%; agreement between any two labelling sessions, 89.03%), the authors suggest its implementation in the clinical routine. The method presented in this article was implemented in jMRUI's SpectrIm plugin. Copyright © 2016 John Wiley & Sons, Ltd.

The Economic Case for Fiscal Federalism in Scotland

In this paper we consider the case for assigning tax revenues to Scotland, by which we mean that taxes levied on Scottish tax bases should be returned to the Scottish budget. The budget, however, would continue to be supplemented by transfers from the Westminster budget. This arrangement differs from the current situation whereby public spending is largely financed by a bloc grant from Westminster. Our suggestion falls short of full fiscal federalism for Scotland . meaning that Scotland had control over choice of tax base and of tax rates, and fiscal transfers from Westminster would be minimal. We use propositions drawn from the theory of fiscal federalism to argue for a smaller vertical imbalance between taxes retained in Scotland and public spending in Scotland. A closer matching of spending with taxes would better signal to beneficiaries the true costs of public spending in terms of taxes raised. It would also create more complete incentives for politicians to provide public goods and services in quantities and at qualities that voters are actually willing to pay for. Under the current bloc grant system, the marginal tax cost of spending does not enter into political agents. calculations as spending is out of a fixed total budget. Moreover, the Scottish electorate is hindered in signaling its desire for local public goods and services since the size of the total budget is determined by a rigid formula set by Westminster. At the present time we reject proposals for full fiscal federalism because in sharply reducing vertical imbalance in the Scottish budget, it is likely to worsen horizontal balance between Scotland and the other UK regions. Horizontal balance occurs where similarly situated regions enjoy the same per capita level of public goods and services at the same per capita tax cost. The complete removal of the bloc grant under full fiscal federalism would remove the mechanism that currently promotes horizontal equity in the UK. Variability in own-source tax revenues creates other problems with full fiscal federalism. Taxes derived from North Sea oil would constitute a large proportion of Scottish taxes, but these are known to be volatile in the face of variable oil prices and the pound-dollar exchange rate. At the present time variability in oil tax revenue is absorbed by Westminster. Scotland is insulated through the bloc grant. This risk sharing mechanism would be lost with full fiscal federalism. It is true that Scotland could turn to financial markets to tide itself over oil tax revenue downturns, but as a much smaller and less diversified financial entity than the UK as a whole it would probably have to borrow on less favorable terms than can Westminster. Scotland would have to bear this extra cost itself. Also, with full fiscal federalism it is difficult to see how the Scottish budget could be used as a macroeconomic stabilizer. At present, tax revenue downturns in Scotland - together with the steady bloc grant - are absorbed through an increase in vertical imbalance. This acts as an automatic stabilizer for the Scottish economy. No such mechanism would exist under full fiscal federalism. The borrowing alternative would still exist but on the less favorable terms - as with borrowing to finance oil tax shortfalls.

Automatic Stabilizer Feature of Fixed Exchange Rate Regimes in Emerging Markets

This paper shows that countries characterized by a financial accelerator mechanism may reverse the usual finding of the literature -- flexible exchange rate regimes do a worse job of insulating open economies from external shocks. I obtain this result with a calibrated small open economy model that endogenizes foreign interest rates by linking them to the banking sector's foreign currency leverage. This relationship renders exchange rate policy more important compared to the usual exogeneity assumption. I find empirical support for this prediction using the Local Projections method. Finally, 2nd order approximation to the model finds larger welfare losses under flexible regimes.

Risk, Transaction Costs, and Tax Assignment: Government Finance in the Ottoman Empire

Risk and transaction costs often provide competing explanations of institutional outcomes. In this paper we argue that they offer opposing predictions regarding the assignment of fixed and variable taxes in a multi-tiered governmental structure. While the central government can pool regional risks from variable taxes, local governments can measure variable tax bases more accurately. Evidence on tax assignment from the mid-sixteenth century Ottoman Empire supports the transaction cost explanation, suggesting that risk matters less because insurance can be obtained in a variety of ways.

Squash Bug, Squash Vine Borer, and Striped Cucumber Beetle on Butternut Squash and Muskmelon

Alternative agricultural schemes are gaining attention as the demand for organic and sustainable products continues to grow. Pest insects pose a sizeable challenge to agricultural production because their activities reduce crop fitness and productivity. Effective management of pest-insects is, therefore, crucial for successful management, and increasingly entails a multi-dimensional approach.