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signal Preprocessing and Artifact Removal for Brain-Computer Interfaces 16

Signal Preprocessing and Artifact Removal for Brain-Computer...

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16th ieee International symposium on Applied computational intelligence and Informatics, SACI 2022

作者： Damian, Miruna-Maria Precup, Radu-Emil Politehnica Univ. Timisoara Aai Department Timisoara Romania

ISBN: (数字)9781665481250

ISBN: (纸本)9781665481250

Brain-Computer Interfaces (BCIs) have become an important research field in the past decades. Interest has grown in this area given the tremendous potential of BCI systems of restoring, replacing, improving, enhancing and supplementing the activity of the central nervous system. Moving from laboratory refined circumstances to portable neuroprosthetics poses great challenges on signal processing and artifact removal. This paper discusses some methods used in signal preparation and preprocessing and also some techniques for artifact removal from electroencephalogram-recorded brain activity. © 2022 ieee.

关键词： Brain computer interface

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Video Face Replacement System Using a Modified Poisson Blending Technique

Video Face Replacement System Using a Modified Poisson Blend...

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International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Afifi, Mahmoud Hussain, Khaled F. Ibrahim, Hosny M. Omar, Nagwa M. Assiut Univ Dept Informat Technol Assiut Egypt Assiut Univ Dept Comp Sci Assiut Egypt

ISBN: (纸本)9781479961207

In this paper, we present a system for video face replacement that requires only two videos of a source actor and a target actor using only a single digital camera. Existing video face replacement techniques usually need special equipment or 3D models;the proposed system achieves a realistic replacement of faces without using 3D models or special equipment. There are many applications of the proposed system that are presented in this paper using only two footages of actors. We can replace a frontal face with another one;this gives the possibility to change the appearance of actors without makeup or any prior settings. We introduce a new technique for face blending that is based on a gradient domain method called Modified Poisson Blending ( MPB) to reduce the bleeding problem of Poisson image editing, and achieve realistic results of face replacement. Experimental results demonstrate that the proposed system using MPB technique produces more realistic results than the results of other cloning techniques.

关键词： image processing image cloning interactive image editing face replacement video compositing

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image fusion based on lifting wavelet transform

Image fusion based on lifting wavelet transform

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International symposium on intelligence Information processing and Trusted Computing

作者： Xiao, Xiaohong Wu, Zhihong College of Computer Science and Technology Huanggang Normal University Huanggang Hubei China

ISBN: (纸本)9780769541969

This paper first introduces the basic principle and implementation steps of lifting wavelet transform. As lifting wavelet transform has advantages like simpler computation, higher execution speed and saving more memory space compared to traditional wavelet transform, it is applied to image fusion so as to obtain better fusion effect and improve fusion speed. Besides, in this paper, different fusion rules are adopted for the high-frequency and low-frequency part after lifting wavelet transform. Finally, the fusion result is compared to that using traditional wavelet transform. Experimental results show that the image fusion method based on lifting wavelet transform has better both subjective and objective effect as well as timeliness. © 2010 ieee.

关键词： image fusion

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Chaldene: Towards Visual Programming image processing in Jupyter Notebooks

Chaldene: Towards Visual Programming Image Processing in Jup...

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2022 ieee symposium on Visual Languages and Human-Centric Computing

作者： Chen, Fei Slusallek, Philipp Mueller, Martin Dahmen, Tim German Res Ctr Artificial Intelligence DFKI Saarbrucken Germany Saarland Univ Saarbrucken Germany

ISBN: (纸本)9781665442152;9781665442145

Jupyter Notebook [1] is an open source, interactive computing platform widely used in the scientific computing and artificial intelligence community [2], [3], [4], [5]. The popularity of the platform is a consequence of the generated single notebook document combining source code, markdown, and visualizations (Fig.1). This makes the platform ideal for tasks such as data analysis and scientific image processing, where repeatability and transparency of analysis tasks are just as important as functionality and performance. However, the obligatory use of code is an obstacle to acceptance of the platform in scientific communities where programming is not generally taught in the curriculum. Consequently, many experimental communities rely on manual image processing using graphical user interfaces [6], [7], [8]. The obvious disadvantages are the lack of repeatability, transparency, and precision in image processing and data analysis tasks. To solve these issues, we propose to extend Jupyter Notebook with visual programming cells. In each visual programming cell, users can create the program by assembling graphical nodes that represent computational instructions, and the textual program is automatically generated and executed by the environment. Cells will support version control aware serialization and deserialization. The core innovation of our proposed work lies in a change of workflow and the adaption of a jupyter-based workflow in experimental communities that have no culture of working with source code. The system can be adapted to multiple applications and domains by integrating new node types. We hereby present an early version of the system and provide one use case from microscopy image processing to demonstrate the integration of existing non-Python software.

关键词： VPL visual programming language graphical programming Jupyter Notebook image processing

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Optimized kernel fuzzy c means (OKFCM) clustering algorithm on level set method for noisy images

Optimized kernel fuzzy c means (OKFCM) clustering algorithm ...

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2013 4th ieee International Conference on computational intelligence and Computing Research, ieee ICCIC 2013

作者： Saikumar, Tara Preetam, I. Neenu Department of ECE CMR Technical Campus JNTUH Hyderabad India Jaipur India

ISBN: (纸本)9781479915972

In this paper, optimized kernel fuzzy c-means (OKFCM) was used to generate an initial contour curve which overcomes leaking at the boundary during the curve propagation. Firstly, OKFCM algorithm computes the fuzzy membership values for each pixel. On the basis of OKFCM the edge indicator function was redefined. Using the edge indicator function the segmentation of medical images which are added with salt and pepper noise was performed to extract the regions of interest for further processing. The results of the above process of segmentation showed a considerable improvement in the evolution of the level set function. © 2013 ieee.

关键词： image segmentation

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A Novel Semi-Automatic Method for Accurate Registration of FDG_CT and FLT_CT image Modalities

A Novel Semi-Automatic Method for Accurate Registration of F...

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2015 ieee signal processing in Medicine and Biology symposium (SPMB)

作者： Wang, Xue Wang, Zhenzhong Wang, Jin Cabrerizo, Mercedes Adjouadi, Malek Goryawala, Mohammed Gulec, Seza A. Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA Univ Miami Miller Sch Med Coral Gables FL 33124 USA Florida Int Univ Herbert Wertheim Coll Med Miami FL 33174 USA

ISBN: (纸本)9781509013500

The widely used 18F-fluorodeoxyglucose (18F-FDG) radiotracer serves as a good imaging tool in Computed Tomography (CT) and is essential for cancer diagnosis as FDG uptake is higher in cancerous lesions and lower in benign ones, while 18F-fluorothymidine (18F-FLT) uptake is shown to be closely correlated with cellular proliferation. The registration of both of these tracers, FDG and FLT, complement one another to increase both sensitivity and specificity for imaging cancer. Accurate registration of both imaging modalities is thus sought in this study to optimize the results of the diagnosis. This paper describes a novel feature-based registration method which employs affine transformation and linear interpolation for FDG_CT and FLT_CT image modalities. Instead of using one set of affine transformation parameters, three slices have been selected to calculate all of the transformation parameters for CT image registration by linear interpolation. This method has the merits of: a) improving the 3D registration results for CT images;b) avoiding arbitrary selection of that one slice for calculating the transformation parameters for registration;and c) being cost-effective in both its implementation and computational requirements. Experimental results show that effective registration of these two imaging modalities could prove very useful for cancer diagnosis, including improved means for quantization and visualization.

关键词： image registration FDG_CT FLT_CT

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BLASTOMERE SEGMENTATION AND 3D MORPHOLOGY MEASUREMENTS OF EARLY EMBRYOS FROM HOFFMAN MODULATION CONTRAST image STACKS

BLASTOMERE SEGMENTATION AND 3D MORPHOLOGY MEASUREMENTS OF EA...

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7th ieee International symposium on Biomedical Imaging: From Nano to Macro

作者： Giusti, Alessandro Corani, Giorgio Gambardella, Luca Magli, Cristina Gianaroli, Luca Dalle Molle Inst Artificial Intelligence Lugano Switzerland Int Inst Reproduct Med Lugano Switzerland

ISBN: (纸本)9781424441266

Monitoring of embryos is an important activity during In Vitro Fertilization (IVF) procedures. A critical stage is that of the early embryo, which is formed by a small number of cells (blastomeres): the morphology of such cells is considered to be a powerful indicator of the embryo viability. We deal with the challenging problem of automatically segmenting the different blastomeres in the early embryo while simultaneously determining their depth, by processing a Z-stack of images acquired by means of an Hoffman Modulation Contrast (HMC) microscope. We discuss experimental results on 53 embryo image stacks, and elaborate on the advantages and limitations of our approach, also briefly describing it is being integrated in the workflow of an IVF laboratory.

关键词： segmentation microscopy In Vitro Fertilization embryo blastomere shape from focus

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Fuzzy logic supported coloured image information enhancement

Fuzzy logic supported coloured image information enhancement

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8th International symposium of Hungarian Researchers on computational intelligence and Informatics, CINTI 2007

作者： Várkonyi-Kóczy, Annamária R. Rövid, András Dept. of Measurement and Information Systems Integrated Intelligent Systems Japanese-Hungarian Laboratory Budapest University of Technology and Economics Hungary

High dynamic range of illumination may cause serious distortions and information loss in the viewing and further processing of digital images. On the other hand, digital processing can often improve the visual quality of real-world photographs or views. Recently, HDR imaging techniques have come into the focus of research because of their high theoretical and practical importance. In this paper, a new fuzzy supported colour tone reproduction algorithm is introduced which may help in developing hardly or non-viewable features and content of colour images. It results in high quality colour HDR images containing the maximum level of details and colour information.

关键词： Fuzzy logic

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Automated Major Depressive Disorder Classification using Deep Convolutional Neural Networks and Choquet Fuzzy Integral Fusion

Automated Major Depressive Disorder Classification using Dee...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Rafiei, Alireza Wang, Yu-Kai Univ Tehran Fac New Sci & Technol Tehran Iran Univ Technol Sydney Sch Comp Sci Australian Artificial Intelligence Inst Ultimo NSW 2007 Australia

ISBN: (纸本)9781665487689

Major depressive disorder (MDD) is a common and severe ailment impacting functional frailty, while its concrete manifestations have been shrouded in mystery. Hence, manual diagnosis of MDD is an arduous and subjective task. Despite the aid of electroencephalogram (EEG) signals in the detection, developing intelligent systems are required to improve clinical utility, performance, and efficiency. In this study, we focus on the automated detection of MDD via raw EEG data using convolutional neural networks (CNN). For this objective, we first extracted the short-time Fourier transform (STFT) of EEG records for five distinct band powers and created an image representing the frequency oscillation of every channel during a resting state. Afterward, we applied three approaches to determine whether a subject is MDD or a Healthy individual. In the first approach, a 2D-CNN model was developed for each band power to detect MDD separately. Second, the outcomes of the developed models were used to establish a Choquet fuzzy integral fusion to classify subjects using all of the previous models. The third approach was dedicated to introducing a 3D-CNN architecture. This model received three-dimensional data by putting different band powers' images together. The two last approaches achieved a 95.65% accuracy and 100% sensitivity to detect MDD. The proposed approaches can help clinicians as straightforward, efficient, and intelligent diagnostic tools for detecting MDD.

关键词： Major depressive disorder (MDD) Deep learning Choquet fuzzy integral fusion EEG signal processing EEG band powers Convolutional neural network (CNN)

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An Efficient Quality Assessment Method for Screen Content image Based on Gabor 5

An Efficient Quality Assessment Method for Screen Content Im...

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5th ieee International Conference on signal and image processing, ICSIP 2020

作者： Huang, Yijing Wang, Miaohui Shenzhen Guangdong China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen University Shenzhen China

ISBN: (纸本)9781728168968

The goal of an objective quality assessment metric is to use a computational model to measure the image visual quality, which consistent with the subjective judgment of the human being. Accurately evaluating the visual quality of the image is an important task under many application scenarios, such as image compression, image reconstruction, and image enhancement. In this paper, we present an accurate full-reference image quality assessment (IQA) metric for screen content (SC) images. Compared to the other classical algorithms, the proposed method is based on convolution operations, which extremely reduced computational complexity. First, the Gabor filter is used to capture the image structure information, usually composed of edges and contours, which is used to understand the image. And then we detect the visual sensitive areas that can attract more attention from the human visual system (HVS). Finally, the map of visual sensitive areas is used for the weighting strategy. Extended experiments on the SIQAD database validate the superiority of the proposed method. Specifically, it is more consistent with subjective evaluation results than the most popular and state-of-the-art IQA metrics and requires lower computational complexity 1. © 2020 ieee.

关键词： image compression

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