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检索条件"任意字段=18th Image Processing: Algorithms and Systems Conference, IPAS 2020"

共 258 条记录，以下是1-10 订阅

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Post-processing of thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological images

Post-Processing of Thresholding or Deep Learning Methods for...

引用

18th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2025

作者： Marczyk, Michal Wrobel, Agata Merta, Julia Polanska, Joanna Department of Data Science and Engineering Silesian University of Technology Gliwice44-100 Poland Yale Cancer Center Yale School of Medicine New HavenCT06511 United States Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Digital pathology allows for the efficient storage and advanced computational analysis of stained histopathological slides of various tissues. Tissue segmentation is a crucial first step of digital pathology aimed at eliminating background, pen markings, and other artifacts, reducing image size, and increasing the efficiency of further analysis. In most cases, color thresholding or deep learning models are used, but their effectiveness is reduced due to complex artifacts and huge color variations between slides. We propose a post processing method to increase the tissue segmentation performance of any initial segmentation algorithm. Using a set of 197 manually annotated histopathological images of breast cancer patients and 63 images of endometrial cancer patients, we tested our method with 3 thresholding techniques and 3 deep learning-based algorithms by calculating the Dice index, Jaccard index, precision, and recall. In both datasets, applying post processing increased precision and recall for thresholding methods and mostly precision for deep learning models. Overall, applying post-processing gave better tissue segmentation performance than initial segmentation methods, significantly increasing Dice and Jaccard indices. Our results proved that thanks to post-processing, the tissue segmentation pipeline is more robust to noises and artifacts commonly present in histopathological images. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： image segmentation

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A Cloud-Edge Integrated Water Extraction Using Superpixel Segmentation 18th

A Cloud-Edge Integrated Water Extraction Using Superpixel Se...

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18th International conference on Wireless Artificial Intelligent Computing systems and Applications, WASA 2024

作者： Zhang, Qingmin Chen, Chen Zhou, Yang Wang, Zhiyi Jin, Fan Lu, Haitao Wan, Shaohua School of Communication Engineering Xidian University Xi’an China Xidian Hangzhou Institute of Technology Hangzhou311231 China The State Grid Jilin Province Electric Power Company Limited Information Communication Company Changchun130000 China National Key Laboratory of Science and Technology on Space Microwave CAST Xi’an710100 China Ningbo Joynext Technology Corporation Ningbo361000 China The Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China

ISBN: (纸本)9783031714665

With the development of the Industrial Internet of things (IIoT) and the proposal of smart water conservancy, the integration of the Internet of things (IoT), edge computing, and computer vision for hydrological information monitoring has become a trend in water conservancy. Difficult to provide comprehensive hydrological data from hydrological observation stations, hydrological forecasting in uninformative basins has become one of the research hotspots. water extraction can provide support for many hydrological monitoring. However, the water is difficult to extract when the water in the near-water image has reflection and water surface ripples. We propose a multi-condition water extraction method based on superpixel segmentation under cloud-edge integration architecture. Firstly, based on the color characteristics of the water and the surrounding vegetation, we propose a reflection processing mechanism. Secondly, we propose a mechanism based on superpixel segmentation for the effect of reflection on water extraction. then, we propose a contour correction mechanism. Finally, the flood-filling algorithm is used to extract the water. We compare the traditional image segmentation algorithm with our proposed segmentation method. the results show that the proposed method outperforms other algorithms in all evaluation metrics. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： image segmentation

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Analyzing Cognitive Patterns in Gifted Children Using MRI and Morphometric Similarity Networks

Analyzing Cognitive Patterns in Gifted Children Using MRI an...

引用

18th International Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2025

作者： Han, Shuning Duan, Feng Vilaseca, Gemma Vilaró, Núria Caiafa, Cesar F. Sun, Zhe Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Catalonia Spain Image Processing Research Group RIKEN Center for Advanced Photonics RIKEN Saitama Wako-Shi Japan Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Psychological Department Oms and Prat school Fundació Catalunya- La Pedrera Catalonia Manresa Spain Oms Foundation Catalonia Manresa Spain Instituto Argentino de Radioastronomıa-CCT La Plata CONICET / CIC-PBA / UNLP Argentina Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Psychiatry University of Cambridge Cambridge United Kingdom

Advances in non-invasive neuroimaging, such as structural magnetic resonance imaging (sMRI), have en abled the construction of structural brain networks (SBNs), allowing in vivo mapping of anatomical connec tions. this study investigates brain network structural differences linked to different intelligence levels in children by individual morphometric similarity networks (MSNs) derived from sMRI data. through group and individual-level analyses, we aim to uncover key topological features associated with cognitive perfor mance and to identify a suitable connection density for SBN analysis. Connection density strongly affects global and nodal topological features, with a range of p = 0.05 to 0.15 recommended for stable and optimal results. Gifted individuals exhibit stronger intra-hemispheric and intra-modular connectivity, a more balanced distribution of left-to-right intra-hemispheric connections, and lower mean versatility, supporting efficient and stable cognitive processing. Moreover, anatomical modularity analyses based on von Economo indicate that higher cognitive performance is linked to enhanced connectivity in specific areas (such as secondary sensory area, motor to association area and secondary sensory to limbic area), alongside selective reduction in cer tain modular connections (such as motor to insular area, association to secondary sensory area and motor to secondary sensory area). Furthermore, topological features, including participation coefficient and local effi ciency, are linked to cognitive performance. these findings provide valuable insights into the SBNs underlying cognitive levels in children. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Brain mapping

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Hyperspectral complex-domain image denoising: cube complex-domain BM3D (CCDBM3D) algorithm 18

Hyperspectral complex-domain image denoising: cube complex-d...

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18th image processing: algorithms and systems conference, ipas 2020

作者： Katkovnik, Vladimir Ponomarenko, Mykola Egiazarian, Karen Shevkunov, Igor Kocsis, Peter Tampere University TampereFIN 33101 Finland

We consider hyperspectral phase/amplitude imaging from hyperspectral complex-valued noisy observations. Block-matching and grouping of similar patches are main instruments of the proposed algorithms. the search neighborhood for similar patches spans both the spectral and 2D spatial dimensions. SVD analysis of 3D grouped patches is used for design of adaptive nonlocal bases. Simulation experiments demonstrate high efficiency of developed state-of-the-art algorithms. © 2020, Society for Imaging Science and Technology

关键词： Hyperspectral imaging

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image Debanding Using Iterative Adaptive Sparse Filtering 18

Image Debanding Using Iterative Adaptive Sparse Filtering

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18th image processing: algorithms and systems conference, ipas 2020

作者： Gadgil, Neeraj J. Song, Qing Su, Guan-Ming Dolby Laboratories Inc. SunnyvaleCA United States

Due to a limited bit-depth representation of pixel values and lossy compression methods, an image may exhibit annoying banding or false-contouring artifact. Existing banding-removal approaches mainly include low pass filtering, dithering and re-quantization. In this paper, we propose an image debanding method that iteratively improves the image using a content-adaptive spatial filter. the filter uses adaptive span based on local width of the band and operates on 1D sparse pixel-window. the input image is filtered in each direction i.e. vertical, horizontal and two diagonals sequentially while offering parallel processing in each direction. the iterative framework gradually improves the quality of filtered image until it converges to the final output. Experimental results show that our proposed method is effective in debanding images. © 2020, Society for Imaging Science and Technology

关键词： Pixels

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CNN-based Classification of Degraded images 18

CNN-based Classification of Degraded Images

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18th image processing: algorithms and systems conference, ipas 2020

作者： Endo, Kazuki Tanaka, Masayuki Okutomi, Masatoshi Tokyo Institute of Technology Tokyo Japan National Institute of Advanced Industrial Science and Technology Tokyo Japan

Classification of degraded images is very important in practice because images are usually degraded by compression, noise, blurring, etc. Nevertheless, most of the research in image classification only focuses on clean images without any degradation. Some papers have already proposed deep convolutional neural networks composed of an image restoration network and a classification network to classify degraded images. this paper proposes an alternative approach in which we use a degraded image and an additional degradation parameter for classification. the proposed classification network has two inputs which are the degraded image and the degradation parameter. the estimation network of degradation parameters is also incorporated if degradation parameters of degraded images are unknown. the experimental results showed that the proposed method outperforms a straightforward approach where the classification network is trained with degraded images only. © 2020, Society for Imaging Science and Technology

关键词： image reconstruction

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ALL-IDB: thE ACUTE LYMPHOBLASTIC LEUKEMIA image DATABASE FOR image processing

ALL-IDB: THE ACUTE LYMPHOBLASTIC LEUKEMIA IMAGE DATABASE FOR...

引用

18th IEEE International conference on image processing (ICIP)

作者： Labati, Ruggero Donida Piuri, Vincenzo Scotti, Fabio Univ Milan Dept Informat Technol I-26013 Crema Italy

ISBN: (纸本)9781457713033

the visual analysis of peripheral blood samples is an important test in the procedures for the diagnosis of leukemia. Automated systems based on artificial vision methods can speed up this operation and increase the accuracy and homogeneity of the response also in telemedicine applications. Unfortunately, there are not available public image datasets to test and compare such algorithms. In this paper, we propose a new public dataset of blood samples, specifically designed for the evaluation and the comparison of algorithms for segmentation and classification. For each image in the dataset, the classification of the cells is given, as well as a specific set of figures of merits to fairly compare the performances of different algorithms. this initiative aims to offer a new test tool to the image processing and pattern matching communities, direct to stimulating new studies in this important field of research.

关键词： Acute lymphoblastic leukemia public image database image segmentation image classification

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Survey of image compression algorithms for ESMO mission

Survey of image compression algorithms for ESMO mission

引用

2011 18th International conference on systems, Signals and image processing, IWSSIP 2011

作者： Gostenčnik, Miha Gačnik, Dejan Kramberger, Iztok University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9789958996610

In this paper we present a general evaluation of image compression algorithms for European Student Moon Orbiter mission for acquiring lunar surface imagery. Evaluations were made on ten different images, processed into various image formats and later reviewed with several objective measurements. As a comparison Set-Partitioning in Hierarchical Trees (SPIHT) algorithm and Discrete Cosine Transform (DCT) algorithm were also evaluated. © 2011 Univ of Sarajevo.

关键词： Discrete cosine transforms

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An expandable image database for evaluation of full-reference image visual quality metrics 18

An expandable image database for evaluation of full-referenc...

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18th image processing: algorithms and systems conference, ipas 2020

作者： Ponomarenko, Mykola Ieremeiev, Oleg Lukin, Vladimir Egiazarian, Karen Tampere University TampereFIN 33101 Finland National Aerospace University Kharkiv61070 Ukraine

Traditional approach to collect mean opinion score (MOS) values for evaluation of full-reference image quality metrics has two serious drawbacks. the first drawback is a nonlinearity of MOS, only partially compensated by the use of rank order correlation coefficients in a further analysis. the second drawback are limitations on number of distortion types and distortion levels in image database imposed by a maximum allowed time to carry out an experiment. One of the largest of databases used for this purpose, TID2013, has almost reached these limitations, which makes an extension of TID2013 within the boundaries of this approach to be practically unfeasible. In this paper, a novel methodology to collect MOS values, with a possibility to infinitely increase a size of a database by adding new types of distortions, is proposed. For the proposed methodology, MOS values are collected for pairs of distortions, one of them being a signal dependent Gaussian noise. A technique of effective linearization and normalization of MOS is described. Extensive experiments for linearization of MOS values to extend TID2013 database are carried out. © 2020, Society for Imaging Science and Technology

关键词： Database systems

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Multichannel image processing system for thermal supervision systems

Multichannel image processing system for thermal supervision...

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18th International conference on Photoelectronics and Night Vision Devices

作者： Zorin, AA Razumova, II Tarkov, VA Siberian Res Inst Opt Syst Novosibirsk 630049 Russia

ISBN: (纸本)0819458287

Foundation principles of multichannel real-time information processing system, which is solving a problem of automatic object tracking, are considered in this work. image processing algorithms, which are used for three-channel system foundation and optimally approaching for system core - Microprocessor Neuro Matrix NM6403 are realized. Information processing is accomplished with using of Hopfield neural network, one 384x288 frame processing time is about 100... 140 ms.

关键词： Data processing Neural networks image processing Automatic tracking Detection and tracking algorithms Evolutionary algorithms Convolution Data analysis image quality Visualization

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