Silesian University of Technology

About: Silesian University of Technology is a education organization based out in Gliwice, Poland. It is known for research contribution in the topics: Microstructure & Alloy. The organization has 5994 authors who have published 18578 publications receiving 175654 citations. The organization is also known as: Politechnika Śląska.

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Abstract: Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.

UCID: an uncompressed color image database

Abstract: Standardised image databases or rather the lack of them are one of the main weaknesses in the field of content based image retrieval (CBIR). Authors often use their own images or do not specify the source of their datasets. Naturally this makes comparison of results somewhat difficult. While a first approach towards a common colour image set has been taken by the MPEG 7 committee 1 their database does not cater for all strands of research in the CBIR community. In particular as the MPEG-7 images only exist in compressed form it does not allow for an objective evaluation of image retrieval algorithms that operate in the compressed domain or to judge the influence image compression has on the performance of CBIR algorithms. In this paper we introduce a new dataset, UCID (pronounced ”use it”) - an Uncompressed Colour Image Dataset which tries to bridge this gap. The UCID dataset currently consists of 1338 uncompressed images together with a ground truth of a series of query images with corresponding models that an ideal CBIR algorithm would retrieve. While its initial intention was to provide a dataset for the evaluation of compressed domain algorithms, the UCID database also represents a good benchmark set for the evaluation of any kind of CBIR method as well as an image set that can be used to evaluate image compression and colour quantisation algorithms.

A benchmark study on the thermal conductivity of nanofluids

Abstract: This article reports on the International Nanofluid Property Benchmark Exercise, or INPBE, in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or “nanofluids,” was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (±10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.

Ion‐Current Rectification in Nanopores and Nanotubes with Broken Symmetry

Abstract: This article focuses on ion transport through nanoporous systems with special emphasis on rectification phenomena. The effect of ion-current rectification is observed as asymmetric current–voltage (I–V) curves, with the current recorded for one voltage polarity higher than the current recorded for the same absolute value of voltage of opposite polarity. This diode-like I–V curve indicates that there is a preferential direction for ion flow. Experimental evidence that ion-current rectification is inherent to asymmetric, e.g., tapered, nanoporous systems with excess surface charge is provided and discussed. The fabrication and operation of asymmetric polymer nanopores, gold nanotubes, glass nanocapillaries, and silicon nanopores are presented. The possibility of tuning the direction and extent of rectification is discussed in detail. Theoretical models that have been developed to explain the ion-current rectification effect are also presented.