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A Pilot Study of Automatic Lung Tumor Segmentation from Positron Emission Tomography images using Standard Uptake Values

A Pilot Study of Automatic Lung Tumor Segmentation from Posi...

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Aparna Kanakatte Jayavardhana Gubbi Nallasamy Mani Tomas Kron David Binns Department of Electrical and Computer Systems Monash University Clayton VIC Australia Department of Electrical and Electronics Engineering University of Melbourne Parville VIC Australia Peter MacCallum Cancer Centre East Melbourne VIC Australia

Positron emission tomography (PET) is a medical imaging procedure that shows the physiological function of an organ or tissue. The role of PET during the past decade has evolved rapidly in the detection of lung tumors but the research on quantitative evaluation of PET images is still in its infancy. PET commonly involves scanning the patient after administration of a radioactive analogue of glucose called fluorodeoxy-glucose (FDG). Tumor cells metabolise more glucose than most normal cells. In PET lung images the heart is often visible and because of its constant pumping of blood it requires more glucose and hence both the tumor and the heart appear brighter than the rest in the PET image. In this paper we present a novel segmentation scheme for detecting the tumor alone in lung PET images using standard uptake values (SUV) and connected component analysis. We perform the segmentation in two steps. In coarse segmentation, a non linear scaling of SUV values is performed and then a threshold is chosen adaptively to convert the gray image into the binary image. Fine segmentation is performed on the coarse segmented data in order to narrow down the region of interest using connected component labeling. To our knowledge no one has used connected component analysis for segmenting PET images. We compare our proposed scheme with several commonly used medical image segmentation techniques like threshold, Sobel edge detector, Laplacian of Gaussian (LoG) edge detector, region growing and SUV based segmentation (applied only to PET as SUV is specific to PET). One of the problems in lung tumor detection is the presence of the heart in the image which accumulates activity and often gets recognized as a hot spot (a probable tumor). All the other segmentation schemes detected both the heart and the tumor as hot spots while our segmentation scheme detected the tumor alone as the hot spot. The preliminary study of the proposed scheme has yielded very promising results and will be stu

关键词： Lung neoplasms image segmentation Positron emission tomography Heart image edge detection Sugar Tumors Biomedical imaging image analysis Detectors

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A radon wigner ville based image dissimilarity measure

A radon wigner ville based image dissimilarity measure

引用

ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Saleem Amina Beghdadi Azeddine Chetouani Aladine B. Boashash L2TI-Institute Galilee Universite Paris Villetaneuse France Qatar University College of Engineering Doha Qatar

In this paper, we introduce a radon wigner ville based image dissimilarity measure. The proposed image distortion measure aims to combine the useful properties of the wigner ville and the directionality of the finite Radon transform for image quality assessment. The results are compared with several HVS and transform based measures of image quality on the basis of complexity of these measures and their consistency with subjective assessment.

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Extracting salient lines by Visual Attention for omnidirectional image classification

Extracting salient lines by Visual Attention for omnidirecti...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： AmirHossein Habibian Majid Nili-Ahmadabadi Babak Nadjar Araabi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Faculty of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences Tehran Iran

Representing an image as a set of its key and interesting lines facilitates the image understanding and classification. In this paper, we propose a method to extract the significant and interesting lines of the scene, which probably are useful in image classification. The proposed method is inspired from the Visual Attention, which is a perceptual mechanism in human and other primates that direct their perceptions to the limited regions of the scene. The attended regions are usually valuable in performing the task. Since the approach of using the lines to classify the images is particularly useful for omnidirectional images, we specialize our method to deal with these kinds of images. In the experiments, we demonstrate how our proposed methods improve the image classification performance with processing only small parts of the input images.

关键词： Feature extraction Visualization image classification Gabor filters image edge detection Histograms computational modeling

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ieee symposium on Foundations of computational intelligence (FOCI'07)

IEEE Symposium on Foundations of Computational Intelligence ...

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ieee symposium on Foundations of computational intelligence, FOCI

The following topics are dealt with: computational intelligence; fuzzy system; evolutionary algorithms; fuzzy classification; real-life computing; lifelog data sensing; lifelog data modeling; artificial immune system; information theoretic learning; neural network learning architecture; granular computing; rough sets; inteval methodologies; evolutionary games; fuzzy sets; fuzzy aggregation; fuzzy logic control; image and signal processing; and fuzzy clustering

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A Flexible Fully-Multiplicative Orthogonal-Group Based ICA Algorithm

A Flexible Fully-Multiplicative Orthogonal-Group Based ICA A...

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ieee symposium on computational intelligence and Bioinformatics and computational Biology (CIBCB)

作者： Yalan Ye Jing Wan Zhi-Lin Zhang Chen Jia Wu Lei School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China Institute of Image Processing and Pattern Recognition Shanghai JiaoTong University Shanghai China

In this paper, we propose a flexible fully-multiplicative orthogonal-group based ICA (FlexibleOgICA) algorithm, which can instantaneously separate the mixture of sub-Gaussian and super-Gaussian source signals. It adopts a self-adaptive nonlinear function, which adjusts its parameter to achieve better performance based on the estimation of the kurtosis of super-Gaussian source signals. We also have successfully applied the algorithm to obtain the fetal electrocardiogram (FECG) signal, showing its fast convergence speed and high separation performance

关键词： Independent component analysis signal processing algorithms Convergence computational intelligence Bioinformatics computational biology signal processing Multidimensional signal processing Biomedical signal processing Switches

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Combination of closest space and closest structure to ameliorate non-local means method

Combination of closest space and closest structure to amelio...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Quoc Bao Do Azeddine Beghdadi Marie Luong L2TI Université Paris 13 Villetaneuse France

Recently non-local means (NLM) has been known to be one of the most attractive denoising algorithms. It alters each pixel by a weighted average of pixels in the image. The weights express the level of similarity between two small patches defined for two involved pixels. There are many propositions to ameliorate the performance of this method. One of branches is to seek the whole image the most similar patches for a given one. In this paper, we investigate this approach and show that it is suitable for only highly textured images. Moreover, we show that combination of this approach and the original NLM yields better result for all image types.

关键词： Pixel Noise reduction Fingerprint recognition image restoration Noise measurement PSNR

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Quality-aware selection of quality factor and scaling parameters in JPEG image transcoding

Quality-aware selection of quality factor and scaling parame...

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ieee symposium on computational intelligence for Multimedia signal and Vision processing, CIMSVP

作者： Stephane Coulombe Steven Pigeon Department of Software and Information Technology Engineering Ecole de Technologie Supérieure Montreal QUE Canada

Reducing the file size of a JPEG image to meet bandwidth or terminal constraints is a common transcoding operation. The reduction can be achieved by reducing either the quality factor (QF) or the resolution, or both. In this paper, we analyze the impact of QF and scaling parameter choices on the quality of the resulting images, as measured by a quality metric such as the structural similarity index (SSIM). We propose a quality-aware transcoding system which considers the quality of transcoded images when QF and scaling are selected jointly. Its goal is to select QF and scaling parameters that maximize the user experience under a given viewing condition, as measured by the chosen quality metric.

关键词： Q factor Transcoding Transform coding image coding image resolution Helium Bit rate Bandwidth image analysis Rendering (computer graphics)

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A 9/7 wavelet-based lossless data hiding

A 9/7 wavelet-based lossless data hiding

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Hui-Yu Huang Shih-Hsu Chang Department of Computer Science and Information Science National Formosa University Yunlin Taiwan Department of Computer Science and Information Science Da-Yeh University Changhua Taiwan

In this paper, a lossless data-hiding approach is presented based on quantized coefficients of discrete wavelet transform (DWT) in the frequency domain to embed secret message. Using the quantized coefficients for 9/7 wavelet filter in DWT, we embed secret data into the successive zero coefficients of the medium-high frequency components in each reconstructed block for 3-level 2-D DWT of a cover-image. The procedures of the proposed system include embedment, extraction, and restoration. Experimental results show that the proposed method can achieve high embedding capacity and acceptable image quality of stego-image, and data reversibility.

关键词： Discrete wavelet transforms Quantization Discrete cosine transforms image restoration image quality Data mining

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Context-based image re-ranking for content-based image retrieval

Context-based image re-ranking for content-based image retri...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Jiyi Li Department of Social Informatics Graduate School of Informatics Kyoto University Japan

In the area of content based image retrieval, people always use the image similarity based on the concrete image parameters like color to rank the images. However the ranking criteria based on image similarity directly is not so significant enough because many images in the given large-scale image database have the approximate similarities to a given image. We propose a graph-based mutual reinforcement method which utilize both of the inter- and intra- relationships among the content and context of the images for re-ranking the similar images. After the re-ranking, we could enlarge the relative-ranking-score-difference of the images, so that the search result becomes more significance. On the other hand our method could also improve the quality of the search result on the metrics such as MAP, recall and precision. The experiments based on the images from the social images hosting websites show the efficiency of our method.

关键词： Context Visualization Measurement image retrieval image color analysis Birds Semantics

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A solution for eigen fuzzy sets of adjoint max-min composition and its application to image analysis

A solution for eigen fuzzy sets of adjoint max-min compositi...

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ieee International symposium on Intelligent signal processing

作者： H. Nobuhara K. Hirota Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Yokohama Japan

As a principal component analysis of the images based on an ordered structure, the greatest eigen fuzzy set (GEFS) and the smallest eigen fuzzy set (SEFS) of max-min composition and adjoint one, are proposed. In the case of the proposed method, an original image is regarded as a fuzzy relation by intensity normalization, and the GEFS and the SEFS are obtained as the transitive closure of the fuzzy relation. Through experiments using 91 test images extracted from 'view sphere database', it is confirmed that the GEFS and SEFS are obtained during 10 iterations, under the condition that the size of the original image is 256 x 256 pixels.

关键词： Fuzzy sets image analysis image processing Testing image databases image coding computational intelligence Principal component analysis Fuzzy systems Medical diagnosis

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