Tom Haeck

ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

&NA; Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non‐invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but the reported results are largely incomparable due to different datasets and evaluation schemes. We approached this urgent problem of comparability with the Ischemic Stroke Lesion Segmentation (ISLES) challenge organized in conjunction with the MICCAI 2015 conference. In this paper we propose a common evaluation framework, describe the publicly available datasets, and present the results of the two sub‐challenges: Sub‐Acute Stroke Lesion Segmentation (SISS) and Stroke Perfusion Estimation (SPES). A total of 16 research groups participated with a wide range of state‐of‐the‐art automatic segmentation algorithms. A thorough analysis of the obtained data enables a critical evaluation of the current state‐of‐the‐art, recommendations for further developments, and the identification of remaining challenges. The segmentation of acute perfusion lesions addressed in SPES was found to be feasible. However, algorithms applied to sub‐acute lesion segmentation in SISS still lack accuracy. Overall, no algorithmic characteristic of any method was found to perform superior to the others. Instead, the characteristics of stroke lesion appearances, their evolution, and the observed challenges should be studied in detail. The annotated ISLES image datasets continue to be publicly available through an online evaluation system to serve as an ongoing benchmarking resource (www.isles‐challenge.org). HighlightsEvaluation framework for automatic stroke lesion segmentation from MRIPublic multi‐center, multi‐vendor, multi‐protocol databases releasedOngoing fair and automated benchmark with expert created ground truth setsComparison of 14+7 groups who responded to an open challenge in MICCAISegmentation feasible in acute and unsolved in sub‐acute cases Graphical abstract Figure. No caption available.

ISLES Challenge 2015: Automated Model-Based Segmentation of Ischemic Stroke in MR Images

We present a novel fully-automated generative ischemic stroke lesion segmentation method that can be applied to individual patient images without need for a training data set. An Expectation Maximization-approach is used for estimating intensity models for both normal and pathological tissue. The segmentation is represented by a level-set that is iteratively updated to label voxels as either normal or pathological, based on which intensity model explains the voxels’ intensity the best. A convex level-set formulation is adopted, that eliminates the need for manual initialization of the level-set. The performance of the method for segmenting the ischemic stroke is summarized by an average Dice score of \(0.78\pm 0.08\) and \(0.53 \pm 0.26\) for the SPES and SISS 2015 training data set respectively and \(0.67\pm 0.24\) and \(0.37 \pm 0.33\) for the test data set.

Using high-amplitude and focused transcranial alternating current stimulation to entrain physiological tremor

Transcranial alternating current stimulation (tACS) is a noninvasive neuromodulation method that can entrain physiological tremor in healthy volunteers. We conducted two experiments to investigate the effectiveness of high-amplitude and focused tACS montages at entraining physiological tremor. Experiment 1 used saline-soaked sponge electrodes with an extra-cephalic return electrode and compared the effects of a motor (MC) and prefrontal cortex (PFC) electrode location. Average peak-amplitude was 1.925 mA. Experiment 2 used gel-filled cup-electrodes in a 4 × 1 focused montage and compared the effects of MC and occipital cortex (OC) tACS. Average peak-amplitude was 4.45 mA. Experiment 1 showed that unfocused MC and PFC tACS both produced phosphenes and significant phase entrainment. Experiment 2 showed that focused MC and OC tACS produced no phosphenes but only focused MC tACS caused significant phase entrainment. At the group level, tACS did not have a significant effect on tremor amplitude. However, with focused tACS there was a significant correlation between phase entrainment and tremor amplitude modulation: subjects with higher phase entrainment showed more tremor amplitude modulation. We conclude that: (1) focused montages allow for high-amplitude tACS without phosphenes and (2) high amplitude focused tACS can entrain physiological tremor.

Publisher Correction: Using high-amplitude and focused transcranial alternating current stimulation to entrain physiological tremor

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