A brief description of CEETI is given, addressing its history, research lines, main scientific results and current
projects

Ferrer, Carlos A.

Lorenzo-Ginori, Juan V.

Taboada-Crispí, Alberto

University of West Bohemia Digital Library

Signal and image processing in the Center of Cuba: center for studies on electronics and information technologies (CEETI)

DSpace at University of West Bohemia

Signal and Image Processing in the Center of Cuba: Center for Studies on Electronics and Information Technologies (CEETI)  Carlos A. Ferrer CEETI, Universidad Central “Marta Abreu” de Las Villas C. Camajuaní, Km 5½ 54830, Santa Clara, Cuba cferrer@uclv.edu.cu Alberto Taboada-Crispí CEETI, Universidad Central “Marta Abreu” de Las Villas C. Camajuaní, Km 5½ 54830, Santa Clara, Cuba  ataboada@uclv.edu.cu Juan V. Lorenzo-Ginori CEETI, Universidad Central “Marta Abreu” de Las Villas C. Camajuaní, Km 5½ 54830, Santa Clara, Cuba  juanl@uclv.edu.cu  ABSTRACT A brief description of CEETI is given, addressing its history, research lines, main scientific results and current projects. Keywords Image Processing, Signal Processing, Cuba. 1. INTRODUCTION The Center for Studies in Electronics and Information Technologies (CEETI) was founded in 1996 with the purpose of developing research projects in the fields of digital image and signal processing (DIP and DSP, respectively). Research activity at CEETI has led to various results, published in refereed scientific journals, a selection of which follows. 2.  IMAGE PROCESSING AT CEETI DIP at CEETI has been performed in response to both practical and theoretical problems. The main areas addressed are shown and commented below. Factors affecting image diagnostic value. The influence of radiologic dosage on image quality was addressed in [Per02] [Per03]. The reduction of the dosage while maintaining image diagnostic value is highly desirable to preserve patient’s health. Expert’s opinions together with ROC analysis were used to establish lower dosage limits without reaching a knee-like point in the ROC curve. The effects of compression on image quality was the topic of [Paz09] in radiologic images, and of [Fal10] for leukocyte images. Lossy compression codecs like JPEG 2000, included in DICOM standard, introduce increasing image distortions as compression rates (CR) gets higher. The effect on a given image depends on its characteristics (color, contrast, noise levels, etc.). For this reason each image type is affected in a different way, and compression limits must be determined on a per-type basis. Fig. 1 illustrates the effect of compression in leukocyte images, as described in [Fal10].   Figure 1: Effect of JPEG 2000 compression on leukocyte images. A: Original 1536H*2048W image. B, C and D: details of a monocyte with CR of 50:1, 100:1, and 200:1, respectively. Again, expert’s opinions and ROC curves were used, this time to determine CR limits. Anomaly detection The complex problem of anomaly detection in images was the content of [Tab09], and an application to cervical cancer detection was described in [Oro13]. In the latter work [Oro13], a preprocessing of the image is performed, based on the saliency concept from biological vision systems. Smear images show a high variability in content, as shown in Fig. 2. A new method for identifying salient regions in pap smear images is proposed and compared to previously reported approaches.  WSCG 2015 Conference on Computer Graphics, Visualization and Computer VisionPoster Proceedings 113 ISBN 978-80-86943-67-1 Figure 2: Left, illustration of background (orange rectangles), cytoplasm (blue) and nuclei (yellow) in Papanicolau test images. Right, difficulties found: touching cells (yellow rectangle) and noise (red rectangles). How such machine-saliency methods can be used to improve human performance in a realistic anomaly detection task is also described. Noise reduction in phase images Noise filtering of phase images was addressed in [Lor02] [Lor07] [Cru09]. An advanced application is reported in [Car02] using quantum-dot cellular automata. Phase images appear in several applications, like magnetic resonance images (MRI) or interferometric synthetic aperture radar (IFSAR). Phase unwrapping in 2D is not uniquely defined, and noise greatly affects its estimation. In [Lor02] several methods and models were proposed and evaluated in terms of the quality of the reconstructed unwrapped phase. In Fig. 3 an example of the results obtained for the best denoising method is shown, for a spherical phantom.   Figure 3 Wraped (top) and unwrapped (bottom) phase images of a spherical phantom. Left: original, center: noisy, right: filtered. Later, other denoising techniques were evaluated (e.g. wavelets in [Cru09]). Cellular Microscopy Research on DIP of cellular microscopy images has led to results reported in various papers, among them in [Oro11] [Lor13] and [Coc14]. In [Oro11], the segmentation of cell nuclei and cytoplasm is required, since the ratio between both areas in a cell is an important feature for cancer diagnosis. Cell nuclei in Papanicolau tests are highly variable in terms of shape and texture, as shown in Fig. 4.  Figure 4: Left, illustration of background, cytoplasm and nuclei in Papanicolau test images. Right: nuclei variability (cyan, red and yellow). This work used a two phase approach for nuclei segmentation, validated against manually segmented images and compared to several state-of-the-art methods. 3. OTHER RELEVANT RESULTS Through its history, CEETI has also reached visibility in research areas other than DIP. Compression, filtering and classification of ECG signals was the main topic in CEETI’s early years [Mor97] [Car98] [Tab99]. EEG signals have also been addressed, either for its compression [Car04] [Baz12a] [Baz12b] or analysis [Rui09] [Rui10] [Rui12]. Speech processing has been an active area of research at CEETI, where most significant results are associated to the measurement of perturbations in pathological speech [Fer05] [Fer09] [Fer10].  Some results have also been obtained in the processing of genomic sequences [Fue07] [Lor09]. General-purpose DSP algorithms and techniques have also been addressed, like noise reduction using wavelets [Can02] or bionic models in classification tasks [Gon10]. 4. CURRENT PROJECTS The line of DIP at CEETI is currently centered in two main topics, one in the detection of anomalies in cell microscopy, and other in neuronal (and arteries/veins) tracing methods. Biomedical applications are still a priority at CEETI. As for other research topics outside DIP (i.e. DSP), pathological speech processing is the strongest line. The usefulness of speech to diagnose a pathology or reflect its severity is being studied on dysphonias, cognitive impairing diseases and sleep apnea, among others. 5. ACKNOWLEDGMENTS The authors wish to acknowledge Dr. Vaclav Skala, for kindly inviting us to WSCG-2015. WSCG 2015 Conference on Computer Graphics, Visualization and Computer VisionPoster Proceedings 114 ISBN 978-80-86943-67-16. REFERENCES [Baz12a] Bazán-Prieto, C., Blanco-Velasco, M., Cárdenas-Barrera, J.L. and Cruz-Roldán, F. Analysis of tractable distortion metrics for EEG compression applications. Physiological measurement 33 No.7, pp. 1237-1247, 2012. [Baz12b] Bazán-Prieto, C., Blanco-Velasco, M., Cárdenas-Barrera, J.L. and Cruz-Roldán, F.Retained energy-based coding for EEG signals. Medical engineering & physics 34 No.7, pp. 892-899, 2012  [Can02] Cancino-de-Greiff, H.F., Ramos-García, R., and Lorenzo-Ginori, J.V. Signal de-noising in magnetic resonance spectroscopy using wavelet transforms, Concepts in Magnetic Resonance 14 No. 6, pp. 388-401, 2002. [Car98] Cárdenas-Barrera, J.L. and Lorenzo-Ginori, J.V. Mean-shape vector quantizer for ECG signal compression. IEEE Transactions on Biomedical Engineering 46 No.1, pp. 62-70, 1998. [Car02] Cárdenas-Barrera, J.L., Plataniotis, K.N. and Venetsanopoulos, A.N. QCA implementation of a multichannel filter for image processing. Mathematical Problems in Engineering 8 No.1 pp. 87-99, 2002. [Car04] Cárdenas-Barrera, J.L., Lorenzo-Ginori, J. V. and Rodríguez-Valdivia, E. A wavelet-packets based algorithm for EEG signal compression. Informatics for Health and Social Care 29 No.1, pp. 15-27, 2004. [Coc14] Coca-Rodríguez, A. and Lorenzo-Ginori, J V. Effects of Interpolation on Segmentation in Cell Imaging. Computación y Sistemas 18 No.1, pp. 97-109, 2014.  [Cru09] Cruz-Enríquez, H. and Lorenzo-Ginori, J. V. Combined Wavelet and Nonlinear Filtering for MRI Phase Images. Lecture Notes in Computer Science LNCS 5627, pp. 83–92, 2009. [Fal10] Falcón-Ruiz, A., Paz-Viera, J. and H Sahli Estimating Quality Bounds of JPEG 2000 Compressed Leukocytes Images. Lecture Notes in Computer Science LNCS 6256, pp. 107-114, 2010. [Fer05] Ferrer, C., González, E. and Hernández-Díaz, M. E. Correcting the use of ensemble averages in the calculation of Harmonics to Noise Ratios in voice signals. Journal of the Acoustical Society of America 18, No.2, pp. 605-608, 2005. [Fer09] Ferrer, C., González, E., Hernández-Díaz, M. E., Torres, D. and del-Toro, A. Removing the Influence of Shimmer in the calculation of Harmonics-to-Noise Ratios using Ensemble-Averages in Voice Signals. EURASIP Journal on Advances in Signal Processing, 2009:784379, 2009. [Fer10] Ferrer, C., Torres, D., and Hernández-Díaz, M. E. Using dynamic time warping of T0 contours in the evaluation of cycle-to-cycle Pitch Detection Algorithms, Pattern Recognition Letters 31 No.6, pp 517-522, 2010. [Fue07] Fuentes, A., Ginori, J. and Abalo, R. A new predictor of coding regions in genomic sequences using a combination of different approaches. International Journal of Biomedical and Life Sciences 3 No.2, pp. 1-5. 2007. [Gon10] Gonzalez, E., Liljenström, H., Ruiz, Y., and Li, G. A biologically inspired model for pattern recognition. Journal of Zhejiang University SCIENCE B 11 No.2, pp. 115-126, 2010. [Lor02] Lorenzo-Ginori, J.V., Plataniotis, K.N. and Venetsanopoulos, A.N. Nonlinear filtering for phase image denoising. IEE Proceedings on Vision, Image and Signal Processing 149 No.5, 290-296, 2002  [Lor07] Lorenzo-Ginori, J. V. An Approach to the 2D Hilbert Transform for Image Processing Applications. Lecture Notes in Computer Science LNCS 4633, pp. 157-165, 2007. [Lor09] Lorenzo-Ginori, J.V., Rodríguez-Fuentes, A., Abalo, R.G., and Rodríguez, R.S.  Digital signal processing in the analysis of genomic sequences. Current Bioinformatics 4 No.1, pp. 28-40, 2009.  [Lor13] Lorenzo-Ginori, J.V., Curbelo-Jardines, W., López-Cabrera, D. and Huergo-Suárez, S.B. Cervical Cell Classification Using Features Related to Morphometry and Texture of Nuclei. Lecture Notes in Computer Science, LNCS 8259, pp. 222-229, 2013. [Mor97] Morales, R.O., Sánchez, M.A.P, Ginori, J.V.L., Abalo, R.G. and Ramírez, R.R. Evaluation of QRS morphological classifiers in the presence of noise. Computers and Biomedical Research 30 No.3, pp. 200-210, 1997. [Oro11] Orozco-Monteagudo, M. Sahli, H., Mihai, C. and Taboada-Crispí, A. A hybrid approach for Pap-Smear cell nucleus extraction. Pattern Recognition, Lecture Notes in Computer Science LNCS 6718, 2011, pp 174-183, 2011. [Oro13] Orozco-Monteagudo, M, Taboada-Crispi, A., and Sahli, H. Biologically Inspired Anomaly Detection in Pap-Smear Images. Lecture Notes in Computer Science LNCS 8259, pp.17-24, 2013. [Paz09] Paz, J., Pérez, M., Schelkens, P. and Rodríguez, J. Impact of JPEG 2000 compression on lesion detection in MR imaging. Medical Physics 36 No.11, pp. 4967-4976, 2009. WSCG 2015 Conference on Computer Graphics, Visualization and Computer VisionPoster Proceedings 115 ISBN 978-80-86943-67-1[Per02] Diaz, M.P., García, J.Q., Vicente, F.P. and Rizo, O.D. Administered activity optimization in patients studied by equilibrium gated radionuclide ventriculography using pyrophosphate and technetium-99m. Nuclear medicine communications 23 No.4, pp. 347-353, 2002. [Per03] Díaz, M.P., Aparicio, E.E., Rizo, O.D., Díaz, R.R. and Rodríguez, C.H. Administered activity optimization in 99mTc-MAG3 renography for adults. Journal of nuclear medicine technology 31 No.4, pp. 216-221, 2003. [Rui09] Ruiz, Y., Li, G., Freeman, W.J. and Gonzalez, E. Detecting stable phase structures in EEG signals to classify brain activity amplitude patterns. Journal of Zhejiang University SCIENCE A 10 No.10, pp. 1483-1491, 2009. [Rui10] Ruiz, Y., Pockett, S., Freeman, W.J., Gonzalez, E. and Li, G. A method to study global spatial patterns related to sensory perception in scalp EEG. Journal of neuroscience methods 191 No.1, pp. 110-118, 2010. [Rui12] Ruiz, Y., Li, G., Gonzalez, E. and Freeman, W.J. A new approach to detect and study spatial–temporal intracranial EEG frames. Digital Signal Processing 22 No.1, pp. 133-139, 2012. [Tab99] Taboada-Crispi, A., Lorenzo-Ginori, J.V. and Lovely, D.F. Adaptive line enhancing plus modified signal averaging for ventricular late potential detection. Electronics Letters 35 No.16, 1293-1295, 1999. [Tab09] Taboada-Crispi, A., Sahli, H., Orozco-Monteagudo, M., Hernandez-Pacheco, D. and Falcon-Ruiz, A. Anomaly Detection in Medical Image Analysis, pp 426-446, in: Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications, 2009.  WSCG 2015 Conference on Computer Graphics, Visualization and Computer VisionPoster Proceedings 116 ISBN 978-80-86943-67-1

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Signal and image processing in the Center of Cuba: center for studies on electronics and information technologies (CEETI)

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