# Andrzej Skalski

PhD
AGH University of Science and Technology in Kraków · Department of Measurement and Electronics
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## Research experience

• Oct 2005–
present
##### Research: AGH University of Science and Technology in Kraków
AGH University of Science and Technology in Kraków · Department of Measurement and Electronics
Poland · Kraków

## Education

• Oct 2005–
Nov 2009
##### AGH University of Science and Technology in Kraków
Biocybernetics and Biomedical Engineering · PhD
Poland · Krakow
• Oct 2000–
Sep 2005
##### AGH University of Science and Technology in Kraków
Electrical Engineering - Measurement and Instrumentation · Msc
Poland · Krakow

• Languages
English

## Questions and Answers (5) View all

4 Features in an image?
· Staffordshire University
Andrzej Skalski · AGH University of Science and Technology in Kraków
You can use Harris detectors, HOG, it depends on what object and what kind of images you have. You can also think about more complex solution like ASM... [more]
• 14 Any recommendation for non rigid objects registration?
· University of Science, Malaysia
Andrzej Skalski · AGH University of Science and Technology in Kraków
If you have a segmented objects on images and you want to find deformed object on other image you can use ASM or AAM (you can download code from Matl... [more]
7 Correlation in MATLAB programming: It returns a matrix. I just need it to return the unique number. Is it possible?
· University of Tehran
Andrzej Skalski · AGH University of Science and Technology in Kraków
b is in [-1 1] range, 1 is a perfect correlation. The + and  - signs are used for positive linear correlations and negative linear correlations, res... [more]
7 Correlation in MATLAB programming: It returns a matrix. I just need it to return the unique number. Is it possible?
· University of Tehran
Andrzej Skalski · AGH University of Science and Technology in Kraków
Try to use, correlation coefficient -> corrcoef. You receive a matrix which indicate how one signal are correlated with second. As result you received... [more]
5 Histogram IN C# or in matlab!
· Indian Institute of Space Science and Technology
Andrzej Skalski · AGH University of Science and Technology in Kraków
If I is you image n by m by 3 then (in matlab): figure subplot(131) imhist(I(:,:,1)); %R subplot(132) imhist(I(:,:,2)); %G subplot(133) imhist(... [more]

## Publications (16) View all

• ##### Article:Automatic tracking of implanted fiducial markers in cone beam CT projection images.
[show abstract] [hide abstract]
ABSTRACT: This paper describes a novel method for simultaneous intrafraction tracking of multiple fiducial markers. Although the proposed method is generic and can be adopted for a number of applications including fluoroscopy based patient position monitoring and gated radiotherapy, the tracking results presented in this paper are specific to tracking fiducial markers in a sequence of cone beam CT projection images. The proposed method is accurate and robust thanks to utilizing the mean shift and random sampling principles, respectively. The performance of the proposed method was evaluated with qualitative and quantitative methods, using data from two pancreatic and one prostate cancer patients and a moving phantom. The ground truth, for quantitative evaluation, was calculated based on manual tracking preformed by three observers. The average dispersion of marker position error calculated from the tracking results for pancreas data (six markers tracked over 640 frames, 3840 marker identifications) was 0.25 mm (at iscoenter), compared with an average dispersion for the manual ground truth estimated at 0.22 mm. For prostate data (three markers tracked over 366 frames, 1098 marker identifications), the average error was 0.34 mm. The estimated tracking error in the pancreas data was < 1 mm (2 pixels) in 97.6% of cases where nearby image clutter was detected and in 100.0% of cases with no nearby image clutter. The proposed method has accuracy comparable to that of manual tracking and, in combination with the proposed batch postprocessing, superior robustness. Marker tracking in cone beam CT (CBCT) projections is useful for a variety of purposes, such as providing data for assessment of intrafraction motion, target tracking during rotational treatment delivery, motion correction of CBCT, and phase sorting for 4D CBCT.
Medical Physics 03/2012; 39(3):1322-34. · 2.83 Impact Factor
• Source
##### Article:Heart Segmentation in Echo Images
A. Skalski, P. Turcza
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ABSTRACT: Cardiovascular system diseases are the major causes of mortality in the world. The most important and widely used tool for assessing the heart state is echocardiography (also abbreviated as ECHO). ECHO images are used e.g. for location of any damage of heart tissues, in calculation of cardiac tissue displacement at any arbitrary point and to derive useful heart parameters like size and shape, cardiac output, ejection fraction, pumping capacity. In this paper, a robust algorithm for heart shape estimation (segmentation) in ECHO images is proposed. It is based on the recently introduced variant of the level set method called level set without edges. This variant takes advantage of the intensity value of area information instead of module of gradient which is typically used. Such approach guarantees stability and correctness of algorithm working on the border between object and background with small absolute value of image gradient. To reassure meaningful results, the image segmentation is proceeded with automatic Region of Interest (ROI) calculation. The main idea of ROI calculations is to receive a triangle-like part of the acquired ECHO image, using linear Hough transform, thresholding and simple mathematics. Additionally, in order to improve the images quality, an anisotropic diffusion filter, before ROI calculation, was used. The proposed method has been tested on real echocardiographic image sequences. Derived results confirm the effectiveness of the presented method.
Metrology and Measurement Systems. 01/2011;
• ##### Conference Proceeding:Level set based automatic segmentation of ultrasound echocardiographic images
A. Skalski, T. Zielinski, P. Turcza
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ABSTRACT: In the paper novel application of the level set method to heart .segmentation in ultrasound echocardiography is addressed. In the presented approach region of interest of the ultrasound image is calculated by means of Hough transform and speckle noise is reduced by anisotropic diffusion filter. The method is initially validated on USG-like simulated noisy images.
Signal Processing Algorithms, Architectures, Arrangements, and Applications Conference Proceedings (SPA), 2009; 10/2009
• ##### Conference Proceeding:Analysis of vocal folds movement in high speed videoendoscopy based on level set segmentation and image registration
A. Skalski, T. Zielinki, D. Deliyski
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ABSTRACT: Computer analysis of high-speed videoendoscopy (HSV) recordings is becoming increasingly useful in functional evaluation of vocal fold pathology. In this work we present two new approaches for the vocal fold HSV-based analysis that have not been previously reported. First, segmentation of vocal fold edges is performed in our method using the level set algorithm. Second, having two vocal fold contours (for two images) we find point-to-point matching of them using the image registration method based on B-spline free form deformation. Presented results from analysis of normal vocal folds and folds after laser treatment confirm usefulness of the method.
Signals and Electronic Systems, 2008. ICSES '08. International Conference on; 10/2008
• Source
##### Chapter:Virtual Colonoscopy - Technical Aspects
08/2011; , ISBN: 978-953-307-568-6