Artur Klepaczko

Dr. Artur Klepaczko


Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2009 in Computer Methods and Programs in Biomedicine
Verified
Journal Article
Closed access
PSPiotr Marcin Szczypinski
Piotr Marcin Szczypinski
Michał StrzeleckiMichał Strzelecki
Michał Strzelecki
AMAndrzej Materka
Andrzej Materka
AKArtur Klepaczko
Artur Klepaczko

1 February 2013 in Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Verified
Journal Article
Closed access
Michał StrzeleckiMichał Strzelecki
Michał Strzelecki
PSPiotr Marcin Szczypinski
Piotr Marcin Szczypinski
AMAndrzej Materka
Andrzej Materka
AKArtur Klepaczko
Artur Klepaczko

1 January 2014 in Computer Methods and Programs in Biomedicine
Verified
Journal Article
Closed access
PSPiotr Marcin Szczypinski
Piotr Marcin Szczypinski
AKArtur Klepaczko
Artur Klepaczko
MPMarek Pazurek
Marek Pazurek
PDPiotr Daniel
Piotr Daniel

1 January 2015 in Computers and Electronics in Agriculture
Verified
Journal Article
Closed access
PSPiotr Marcin Szczypinski
Piotr Marcin Szczypinski
AKArtur Klepaczko
Artur Klepaczko
PZPiotr Zapotoczny
Piotr Zapotoczny

1 September 2017
Verified
Conference Paper
Closed access
PSPiotr Marcin Szczypinski
Piotr Marcin Szczypinski
AKArtur Klepaczko
Artur Klepaczko
MKMarcin Kociolek
Marcin Kociolek

16 April 2014 in PLOS ONE
Verified
Journal Article
Open access
PDF file
AKArtur Klepaczko
Artur Klepaczko
PSPiotr Marcin Szczypinski
Piotr Marcin Szczypinski
GDGrzegorz Dwojakowski
Grzegorz Dwojakowski
Michał StrzeleckiMichał Strzelecki
Michał Strzelecki
AMAndrzej Materka
Andrzej Materka
With the development of medical imaging modalities and image processing algorithms, there arises a need for methods of their comprehensive quantitative evaluation. In particular, this concerns the algorithms for vessel tracking and segmentation in magnetic resonance angiography images. The problem can be approached by using synthetic images, where true geometry of vessels is known. This paper presents a framework for computer modeling of MRA imaging and the results of its validation. A new model incorporates blood flow simulation within MR signal computation kernel. The proposed solution is unique, especially with respect to the interface between flow and image formation processes. Furthermore it utilizes the concept of particle tracing. The particles reflect the flow of fluid they are immersed in and they are assigned magnetization vectors with temporal evolution controlled by MR physics. Such an approach ensures flexibility as the designed simulator is able to reconstruct flow profiles of any type. The proposed model is validated in a series of experiments with physical and digital flow phantoms. The synthesized 3D images contain various features (including artifacts) characteristic for the time-of-flight protocol and exhibit remarkable correlation with the data acquired in a real MR scanner. The obtained results support the primary goal of the conducted research, i.e. establishing a reference technique for a quantified validation of MR angiography image processing algorithms.