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Comparison of two automatic cell-counting solutions for fluorescent microscopic images
No full textCell counting in microscopic images is one of the fundamental analysis tools in life sciences, but is usually tedious, time consuming and prone to human error. Several programs for automatic cell countinghavebeendeveloped sofar,butmostof them demand additional training or data input from the user. Most of them do not allow the users to online monitor the counting results, either. Therefore, we designed two straightforward, simple-to-use cell-counting programs that also allow users to correct the detection results. In this paper, we present the CELLCOUNTER and LEARN123 programs for automatic and semiautomatic counting of objects in fluorescent microscopic images (cells or cell nuclei) with a user-friendly interface. Although CELLCOUNTER is based on predefined and fine-tuned set of filters optimized on sets of chosen experiments, LEARN123 uses an evolutionary algorithm to determine the adapt filter parameters based on a learning set of images. CELLCOUNTER also includes an extension for analysis of overlaying images. The efficiency of both programs was assessed on images of cells stained with different fluorescent dyes by comparing automatically obtained results with results that were manually annotated by an expert. With both programs, the correlation between automatic and manual counting was very high (R2 < 0.9), although CELLCOUNTER had some difficulties processing images with no cells or weakly stained cells, where sometimes the background noise was recognized as an object of interest. Nevertheless, the differences between manual and automatic counting were small compared to variations between experimental repeats. Both programs significantly reduced the time required to process the acquired images from hours tominutes. The programs enable consistent, robust, fast and accurate detection of fluorescent objects and can therefore be applied to a range of different applications in different fields of life sciences where fluorescent labelling is used for quantification of various phenomena. Moreover, CELLCOUNTER overlay extension also enables fast analysis of related images thatwouldotherwise require imagemergingforaccurateanalysis, whereas LEARN123’s evolutionary algorithm can adapt counting parameters to specific sets of images of different experimental settings
Visualization of concurrent tones in music with colours
No full textVisualizing music in a meaningful and intuitive way is a challenge. Our aim is to visualize music by interconnecting similar aspects in music and in visual perception. We focus on visualizing harmonic relationships between tones and colours. Related existing visualizations map tones or keys into a discrete set of colours. As concurrent (simultaneous) tones are not perceived as entirely separate, but also as a whole, we present a novel method for visualizing a group of concurrent tones (limited to the pitches of the 12-tone chromatic scale) with one colour for the whole group. The basis for calculation of colour is the assignment of key spanning circle of thirds to the colour wheel. The resulting colour is not limited to discrete set of colours: similar tones, chords and keys have similar colour hue; dissonance and consonance are represented by low and high colour saturation respectively. The proposed method is demonstrated as part of our prototype music visualization system using extended 3-dimensional piano roll notation
CVL OCR DB, an annotated image database of texts in natural scenes, and its usability
No full textText detection and optical character recognition (OCR) in images of natural scenes is a fairly new computer vision area but yet very useful in numerous applicative areas. Although many implementations gain promising results, they are evaluated mostly on the private image collections that are very hard or even impossible to get. Therefore, it is very difficult to compare them objectively. Since our aim is to help the research community in standardizing the evaluation of the text detection and OCR methods, we present CVL OCR DB, a public database of annotated images of text in diverse natural scenes, captured at varying weather and lighting conditions. All the images in the database are annotated with the text region and single character location information, making CVL OCR DB suitable for testing and evaluating both text detection and OCR methods. Moreover, all the single characters are also cropped from the original images and stored individually, turning our database into a huge collection of characters suitable for training and testing OCR classifiers
Matrix factorization-based data fusion for drug-induced liver injury prediction
No full textWe report on a data fusion approach for prediction of outcome of drug-induced liver injury (DILI) in humans from gene expression studies as provided by the CAMDA 2013 Challenge. Our aim was to investigate if the data from all four toxicogenomics studies can be fused together to boost prediction accuracy. We show that recently proposed matrix factorization-based fusion provides an elegant framework for integration of CAMDA and related data sets. Our data fusion approach yields a high cross-validated AUC of 0.819 (in vivo assays), which is above the accuracy of standard machine learning procedures (stacked classification with feature selection). Achieved accuracy is also a substantial improvement of the highest scores on the same data sets reported in CAMDA 2012. Our data analysis shows that animal studies can be replaced with in vitro assays (AUC = 0.799) and that we can predict liver injury in humans from animal data (AUC = 0.811)
BIOMETRIČNA VERIFIKACIJA KOT STORITEV V OBLAKU - PRIMER UPORABE
No full textKo govorimo o avtentikaciji na internetu, v večini primerov še vedno mislimo na gesla. Eden izmed največjih problemov trenutnih avtentikacijskih pristopov je vsekakor dejstvo, da si mora uporabnik zapolniti preveliko število uporabniških imen in gesel, kar vodi k pozabljanju ali uporabi istih uporabniških imen in gesel za različne spletne strani. Rešitev tega problema lahko najdemo v uporabi biometrije. V članku predstavljamo biometrično verifikacijo kot storitev v oblaku in primer uporabe takšne storitve v aplikaciji za preverjanje prisotnosti študentov na predavanju