Fractal Descriptors in the Fourier Domain Applied to Color Texture Analysis

The present work proposes the development of a novel method to provide descriptors for colored texture images. The method consists in two steps. In the first, we apply a linear transform in the color space of the image aiming at highlighting spatial structuring relations among the color of pixels. In a second moment, we apply a multiscale approach to the calculus of fractal dimension based on Fourier transform. From this multiscale operation, we extract the descriptors used to discriminate the texture represented in digital images. The accuracy of the method is verified in the classification of two color texture datasets, by comparing the performance of the proposed technique to other classical and state-of-the-art methods for color texture analysis. The results showed an advantage of almost 3% of the proposed technique over the second best approach.Comment: Chaos, Volume 21, Issue 4, 201

Estimation of lung perfusion and ventilation images by narrowband filtering of 2D MR signals

W pracy przedstawiono wyniki badań dotyczących estymacji map ukrwienia i napowietrzenia płuc człowieka na podstawie analizy sekwencji obrazów 2D rezonansu magnetycznego (RM). Wyniki omówiono na przykładzie obrazów RM płuc w pozycji koronalnej. Opracowano algorytm wyznaczania transmitancji wąskopasmowych filtrów użytych do rozdzielenia informacji o ukrwieniu i napowietrzeniu płuc, w oparciu o analizę sekwencji obrazów RM. Zaproponowano ilościową miarę jakości estymowanych map ukrwienia i napowietrzenia.The paper presents results of research on the estimation of lungs perfusion and ventilation by analysis of 2D magnetic resonance (MR) lung images sequence. The results are presented for lung images in coronal view. An algorithm based on an analysis of lung images sequence, for determining narrow band filters used to separate the perfusion and ventilation information, was elaborated. In this work, a quantitative measure of the quality of the estimated perfusion and ventilation was proposed

On diversity within operators' EEG responses to LED-produced alternate stimulus in SSVEP BCI

This work is an attempt to identify causes of the widely observed fact that performance of Brain-Computer Interface systems based on Steady-State Visual Evoked Potentials varies between different users. The efficient LED-produced alternate stimulus systems are taken into account. The effect of stimulus color and flickering frequency on measured SSVEP response at first and second harmonics is investigated for 10 women and 11 men. The experimental setup is described, measurement procedure, signal processing and analysis algorithms are outlined. The results are presented and discussed. One of the early conclusions drawn from this extensive research is that the promising strategy of SSVEP-based BCI system optimization for best performance can be through stimulus adjustment to each individual user

Evaluation of level set method in segmentation of 3D digital phantom images and brain vessels TOF-SWI MR images

W pracy zbadano dokładność metody segmentacji level set stosowanej do analizy trójwymiarowych obrazów fantomów przedstawiających fragmenty naczyń oraz układ drzew krwionośnych. Badano przydatność metody do detekcji cienkich naczyń (o średnicy mniejszej niż rozmiar woksela obrazu) oraz jej odporność na zakłócenia. Oceny metody dokonano za pomocą obiektywnej miary ilościowej opisującej dokładność segmentacji. Metodę level set wykorzystano również do segmentacji rzeczywistych trójwymiarowych obrazów TOF-SWI (Time Of Flight and Susceptibility Weighted Imaging) rezonansu magnetycznego naczyń krwionośnych mózgu wraz z metodą Sato, wykorzystującą filtrację wieloskalową. Wstępne wyniki, w postaci trójwymiarowych modeli naczyń krwionośnych, są obiecujące. W pracy przedstawiono kierunki dalszych badań prowadzących do uzyskania dokładniejszych modeli układu krwionośnego, zwłaszcza dla naczyń o małych średnicach.The objective of this work is to evaluate performance of the level set approach applied to segmentation of 3D images of computer-simulated blood-vessel phantoms and artificial vascular trees. The segmentation of thin vessels with diameter smaller than voxel size and influence of noise on segmentation results, were studied. Quantitative measures of segmentation accuracy were used for the methods evaluation. The level set technique was also used for segmentation of 3D TOF-SWI MR (Time Of Flight and Susceptibility Weighted Magnetic Resonance Imaging) brain vessels images. Also, the multiscale filtering approach was applied. Preliminary results in the form of 3D vein and artery models are promising. Further work aimed at more accurate modeling of brain vasculature, focused on thin vessels detection is also addressed

Segmentation of 3D ToF-SWI brain vessels images by means of multiscale filtering

W pracy przedstawiono wyniki bada ń dotyczących trójwymiarowych metod analizy obrazów 3D rezonansu magnetycznego naczyń krwionośnych mózgu. Scharakteryzowano sekwencje sygnałów skanera MM (rezonansu magnetycznego) wykorzystywane do uzyskania obrazów angiograficznych mózgu. Przedstawiono również wyniki segmentacji drzewa naczyń z wykorzystaniem filtracji wieloskalowej oraz elementów morfologii matematycznej. Przedstawiono kierunki przyszłych badań prowadzących do opracowania połączenia między analizą makro- i mikronaczyń, celem uzyskania dokładniejszych modeli układu krwionośnego.The paper presents the analysis c f 3 0 ToF-SWI magnetic resonance images of brain vessels. T h e MR (magnetic resonance) sequences of ToF (Time of Flight) and SWI (Susceptibility Weighted Imaging) used for acquisition of vasculature images, were characterized. The segmentation results of vessel images, based on muitiscale filtering and mathematical morphology methods, were presented and discussed. Finally, more precise and accurate brain vasculature model, was introduced

Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic resonance imaging

[EN] The purpose of this study was to differentiate acute from chronic myocardial infarction using machine learning techniques and texture features extracted from cardiac magnetic resonance imaging (MRI). The study group comprised 22 cases with acute myocardial infarction (AMI) and 22 cases with chronic myocardial infarction (CMI). Cine and late gadolinium enhancement (LGE) MRI were analyzed independently to differentiate AMI from CMI. A total of 279 texture features were extracted from predefined regions of interest (ROIs): the infarcted area on LGE MRI, and the entire myocardium on cine MRI. Classification performance was evaluated by a nested cross-validation approach combining a feature selection technique with three predictive models: random forest, support vector machine (SVM) with Gaussian Kernel, and SVM with polynomial kernel. The polynomial SVM yielded the best classification performance. Receiver operating characteristic curves provided area-under-thecurve (AUC) (mean +/- standard deviation) of 0.86 +/- 0.06 on LGE MRI using 72 features; AMI sensitivity = 0.81 +/- 0.08 and specificity = 0.84 +/- 0.09. On cine MRI, AUC = 0.82 +/- 0.06 using 75 features; AMI sensitivity = 0.79 +/- 0.10 and specificity = 0.80 +/- 0.10. We concluded that texture analysis can be used for differentiation of AMI from CMI on cardiac LGE MRI, and also on standard cine sequences in which the infarction is visually imperceptible in most cases.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grant BFU2015-64380-C2-2-R, by Instituto de Salud Carlos III and FEDER funds under grants FIS PI14/00271 and PIE15/00013 and by the Generalitat Valenciana under grant PROMETEO/2013/007. The first author, Andres Larroza, was supported by grant FPU12/01140 from the Spanish Ministerio de Educacion, Cultura y Deporte (MECD).Larroza, A.; Materka, A.; López-Lereu, M.; Monmeneu-Menadas, J.; Bodi, V.; Moratal, D. (2017). Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic resonance imaging. European Journal of Radiology. 92:78-83. https://doi.org/10.1016/j.ejrad.2017.04.024S78839

Performance Evaluation of Heart Sound Cancellation in FPGA Hardware Implementation for Electronic Stethoscope

This paper presents the design and evaluation of the hardware circuit for electronic stethoscopes with heart sound cancellation capabilities using field programmable gate arrays (FPGAs). The adaptive line enhancer (ALE) was adopted as the filtering methodology to reduce heart sound attributes from the breath sounds obtained via the electronic stethoscope pickup. FPGAs were utilized to implement the ALE functions in hardware to achieve near real-time breath sound processing. We believe that such an implementation is unprecedented and crucial toward a truly useful, standalone medical device in outpatient clinic settings. The implementation evaluation with one Altera cyclone II-EP2C70F89 shows that the proposed ALE used 45% resources of the chip. Experiments with the proposed prototype were made using DE2-70 emulation board with recorded body signals obtained from online medical archives. Clear suppressions were observed in our experiments from both the frequency domain and time domain perspectives