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Combine unlabeled with labeled MR images to measure acute ischemic stroke lesion by stepwise learning

IET IMAGE processING 2022年第14期16卷 3965-3976页

作者： Zhao, Bin Liu, Zhiyang Liu, Guohua Wu, Mengran Cao, Chen Jin, Song Wu, Hong Ding, Shuxue Nankai Univ Tianjin Key Lab Optoelect Sensor & Sensing Networ Coll Elect Informat & Opt Engn Tianjin 300350 Peoples R China Guilin Univ Elect Technol Sch Artificial Intelligence Guilin Guangxi Peoples R China Tianjin Huanhu Hosp Key Lab Cerebral Artery & Neural Degenerat Tianji Dept Med Imaging Tianjin Peoples R China

Acute ischemic stroke is a common threat to human health and may obtain timely treatment by fast localizing and quantitatively evaluating the lesions. Most CNN-based methods try to segment and measure the lesions, however, they require a training on a large number of labeled subjects that are labor-intensive and time-consuming to obtain. In this paper, a method is proposed that can combine limited labeled subjects with abundant unlabeled subjects to alleviate the problem. The proposed method consists of two stages: stepwise learning process and segmentation process. Stepwise learning is used to obtain the pretrained encoder. The pretrained encoder and the proposed decoder are connected into a new end-to-end segmentation network, which is retrained on the labeled subjects in the segmentation process. By using 5 labeled subjects and 79 unlabeled subjects, the proposed method achieves a mean dice coefficient of 0.663 +/-$\,{\pm}\,$0.205, a mean average symmetric surface distance (ASSD) of 2.17 mm and a mean 95 percentile Hausdorff distance (HD) of 18.38 mm on a clinical MR dataset with 179 subjects. More importantly, it achieves lesion-wise F-1 score of 0.857 and a subject-wise detection rate of 0.966.

关键词： end-to-end segmentation network medical image processing convolutional neural nets image segmentation labeled MR image unlabeled MR image CNN acute ischemic stroke lesion biomedical MRI stepwise learning process learning (artificial intelligence) encoder-decoder diseases segmentation process

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Cooperative object segmentation and recognition via restricted Boltzmann machine

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ELECTRONICS LETTERS 2020年第8期56卷 378-379页

作者： Huang, Wei Yu, Huimin Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ State Key Lab CAD & CG Hangzhou 310027 Peoples R China

The authors present a model where object segmentation and recognition are connected with a bottom-up inference and a top-down generation pathway so that the two models can communicate and cooperate with each other. They are integrated into an energy function and optimised at the same time. To achieve the cooperation, objects are modelled in two aspects: shape and appearance, so that the recognition result could feedback to the segmentation process. Restricted Boltzmann machine is employed to learn the shapes of the objects with corresponding labels and perform object recognition based on the object shapes. Another pathway involved with the appearance knowledge of the objects is also established so that both the shape and appearance information will guide and constrain the evolution of the segmentation developing towards the region of interest, which will further facilitate the performances of both tasks. Experiments demonstrate the effectiveness of the proposed model.

关键词： Boltzmann machines image segmentation object recognition learning (artificial intelligence) recognition result segmentation process object recognition object shapes appearance knowledge appearance information restricted Boltzmann machine generation pathway energy function cooperative object segmentation bottom-up inference top-down generation pathway

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Direct Estimation of Appearance Models for segmentation

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SIAM JOURNAL ON IMAGING SCIENCES 2022年第1期15卷 172-191页

作者： Rocha Neto, Jeova F. S. Felzenszwalb, Pedro Vazquez, Marilyn Brown Univ Sch Engn Providence RI 02912 USA Ohio State Univ Math Biosci Inst Columbus OH 43210 USA

Image segmentation algorithms often depend on appearance models that characterize the distribution of pixel values in different image regions. We describe a new approach for estimating appearance models directly from an image, without explicit consideration of the pixels that make up each region. Our approach is based on novel algebraic expressions that relate local image statistics to the appearance of spatially coherent regions. We describe two algorithms that can use the aforementioned algebraic expressions to estimate appearance models directly from an image. The first algorithm solves a system of linear and quadratic equations using a least squares formulation. The second algorithm is a spectral method based on an eigenvector computation. We present experimental results that demonstrate the proposed methods work well in practice and lead to effective image segmentation algorithms.

关键词： image segmentation mixture models Markov random fields segmentation process

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Fully-automatic raw G-band chromosome image segmentation

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IET IMAGE processING 2020年第9期14卷 1920-1928页

作者： Altinsoy, Emrecan Yang, Jie Yilmaz, Can Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai Peoples R China Shanghai Jiao Tong Univ Inst Med Robot Shanghai Peoples R China

Analysis of the chromosome images plays an important role in discovering one's genetic information and possible genetic disorders. segmentation has a very substantial place in the chromosome analysis and without an automatic solution, it is a time-consuming and error-prone procedure. Many researchers tried to automate the segmentation process. However, background noise, objects other than chromosomes in the image, touching and overlapped chromosomes are still current issues. To address these issues, the authors proposed fully-automatic raw G-band chromosome image segmentation, which aims to segment every single chromosome with a minimal error. The proposed algorithm contains the following steps: clearing the background noise, eliminating the objects other than chromosomes, distinguishing single chromosomes and chromosome clusters, separating touching and overlapping chromosomes. The proposed algorithm is tested on 508 raw images and achieved an accuracy of 94.7% for touching chromosome separation, 96.3% for overlapped chromosome separation, and 98.94% for segmentation of all chromosomes. The whole segmentation process takes 2-7 s for one image, depending on the number of touching and overlapping chromosomes. The segmentation results showed that compared to the previously proposed methods, their algorithm achieved better accuracy.

关键词： image segmentation genetics cellular biophysics bioinformatics overlapped chromosomes fully-automatic raw G-band chromosome image segmentation background noise chromosome clusters touching overlapping chromosomes raw images overlapped chromosome separation segmentation process chromosome analysis single chromosome segmentation time 2 0 s to 7 0 s

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Single-crossover recombination and ancestral recombination trees

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JOURNAL OF MATHEMATICAL BIOLOGY 2014年第6期68卷 1371-1402页

作者： Baake, Ellen von Wangenheim, Ute Univ Bielefeld Fac Technol D-33594 Bielefeld Germany

We consider the Wright-Fisher model for a population of individuals, each identified with a sequence of a finite number of sites, and single-crossover recombination between them. We trace back the ancestry of single individuals from the present population. In the limit without rescaling of parameters or time, this ancestral process is described by a random tree, whose branching events correspond to the splitting of the sequence due to recombination. With the help of a decomposition of the trees into subtrees, we calculate the probabilities of the topologies of the ancestral trees. At the same time, these probabilities lead to a semi-explicit solution of the deterministic single-crossover equation. The latter is a discrete-time dynamical system that emerges from the Wright-Fisher model via a law of large numbers and has been waiting for a solution for many decades.

关键词： Population genetics Recombination segmentation process Ancestral trees Subtree decomposition

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Beyond rhyme or reason: ERPs reveal task-specific activation of orthography on spoken language

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BRAIN AND LANGUAGE 2011年第3期116卷 116-124页

作者： Pattamadilok, Chotiga Perre, Laetitia Ziegler, Johannes C. Univ Libre Bruxelles Unite Rech Neurosci Cognit UNESCOG B-1050 Brussels Belgium Univ Lille 3 Unite Rech Sci Cognit & Affect F-59653 Villeneuve Dascq France CNRS Lab Psychol Cognit F-75700 Paris France Aix Marseille Univ Marseille France

Metaphonological tasks, such as rhyme judgment, have been the primary tool for the investigation of the effects of orthographic knowledge on spoken language. However, it has been recently argued that the orthography effect in rhyme judgment does not reflect the automatic activation of orthographic codes but rather stems from sophisticated response strategies. Such a claim stands in sharp contrast with recent findings using event-related brain potentials (ERPs) in lexical and semantic tasks, which were taken to suggest that orthographic information occurs early enough to affect the core process of lexical access. Here, we show that the electrophysiological signature of the orthography effect in rhyme judgment is indeed different from the one obtained in online lexical or semantic tasks. That is, we did not find the orthography effect in the 300-350 ms time window which has previously been shown to process lexical information in the lexico-semantic tasks, but the effect appeared within the 175-250 ms and the 375750 ms time-windows which we interpreted to reflect segmentation and decisional process, respectively. We conclude that the interactions between phonology and orthography are task-specific. Metaphonological tasks appear of limited use for studying the core processes and interactions that underlie lexical access. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Orthographic effect Metaphonological tasks Rhyme judgment segmentation process Decisional/comparison process Speech recognition tasks Task-specific ERPs

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A perceptual aid to delineating the extent of potential mammographic abnormalities

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BREAST CANCER RESEARCH 2015年第Sup1期17卷 1-13页

作者： Selvan, Arul Chen, Yan Gale, Alastair Sheffield Hallam Univ Sheffield S Yorkshire England Univ Loughborough Loughborough Leics England

P19

关键词： Learning Objective Paired Image segmentation process Breast Screening DICOM Image

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Text-Graphics Separation to Detect Logo and Stamp from Color Document Images: A Spectral Approach 13

Text-Graphics Separation to Detect Logo and Stamp from Color...

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13th IAPR International Conference on Document Analysis and Recognition (ICDAR)

作者： Nandedkar, Amit Vijay Mukhopadhyay, Jayanta Sural, Shamik IIT Kharagpur Sch Informat Technol Kharagpur W Bengal India IIT Kharagpur Dept Comp Sci & Engn Kharagpur W Bengal India

ISBN: (纸本)9781479918058

Text and graphics separation is an important task in the field of document image processing. This work aims at detecting graphics such as logos and stamps in a scanned document image. A novel spectral filtering based text-graphics separation algorithm (SFTGS) is presented here. The property of text that it is the major source of high spatial frequency components in a document image, is exploited in this algorithm. Accordingly high frequency filtering is used to separate the text symbols. This is followed by a segmentation process for delineating residual text and the graphics. The main advantage of SFTGS is that it works in a single pass, and can discriminate graphics and text without supervised training. Subsequently, the graphics segments are further categorized into two different classes, namely logos and stamps. In this case, we assume that these are the two classes of graphical objects present in the documents. The technique is evaluated using publicly available document dataset consisting of graphics as stamps and logos. The result is compared with existing approaches reported in the literature, and it is found that the proposed method performs superior to them. An overall performance of 89.1% recall and 96.9% precision is obtained for SFTGS.

关键词： document image processing image colour analysis image filtering image segmentation spectral analysis text detection SFTGS color document images high frequency filtering high spatial frequency components logo detection residual text delineation scanned document image processing segmentation process spectral approach spectral filtering based text-graphics separation algorithm stamp detection text symbols Artificial intelligence Filtering Graphics Image color analysis Image resolution Image segmentation Yttrium image colour analysis graphic images document image image segmentation document image processing image filtering image resolution LOGO Filtration Rare earths yttrium Artificial Intelligence Spectrum Analysis stamp texts

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Bridging Industrial segmentation Theory and Practice

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JOURNAL OF BUSINESS-TO-BUSINESS MARKETING 2009年第4期16卷 343-373页

作者： Clarke, Ann Hojbjerg Univ So Denmark Dept Entrepreneurship & Relationship Management DK-6000 Kolding Denmark

Purpose segmentation is seen today as a core concept within mainstream marketing. While industrial segmentation has received considerable attention within academic literature, there have been many reports on companies having problems using, applying, and implementing the principles of segmentation. Authors criticize the literature on segmentation forgiving too little attention to implementation, providing marketers little help and guidance on bow to make segmentation work in a practical environment. This article addresses some of these problems. Methodology/Approach: The objective of this article is to design a process with methods and activities for segmentation by building on action research case study data from a large Danish industrial company. Findings: Along with important considerations, this article presents the process of segmentation using a build-up approach based on qualitative market data. The process is practical and easily approachable for companies. The purpose behind segmentation is strategic-identify target segments and facilitate the planning of future product offers. It is argued that segmentation should be dedicated to the purpose and context of the company. This case illustrates how the company adapted segmentation theory to their particular needs.

关键词： Industrial segmentation product development action research segmentation process

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Optical Fish Estimation and Detection in Noisy Environment

Optical Fish Estimation and Detection in Noisy Environment

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Oceans Conference

作者： Boudhane, Mohcine Badri-Hoeher, Sabah Nsiri, Benayad Univ Appl Sci Fac Comp Sci & Elect Engn Grenzstr 5 D-24149 Kiel Germany Univ Hassan 2 Fac Sci Casablanca 20000 Morocco

ISBN: (纸本)9781479949182

Detecting fish in submarine environment is a challenge due to the properties of the water such as light absorption and scattering. In this work, we present a method for preprocessing images in submarine environment. In the first step, we model the underwater environment as overlapp of two processes. The first process is considered as a Poisson distribution, while the second one is considered as a Gaussian mixture. The resulting distribution is called Poisson-Gaussian mixture (PGM). To estimate the noise parameters, we propose an iterative algorithm based on the expectation maximization approach. This allows us to jointly estimate the scale of the Poisson parameter as well as the standard deviation and the mean of all Gaussian distributions. In order to facilitate the detection of objects, to correct the illumination problem of the scene and to restore the colors, we integrate a color correction algorithm. Finally, detection and localization of fish complete the pre-processing in the images. To obtain medium or small regions, the mean shift algorithm is used with a reduced threshold. In the segmentation process, the proposed detector scan the image region by region. This detector allows to estimate statistically the type of the region (object or non-object). The method is tested under different underwater conditions. Experimental results show that the proposed approach outperforms conventional methods.

关键词： Gaussian processes Poisson distribution expectation-maximisation algorithm geophysical image processing image restoration image segmentation iterative methods light absorption light scattering object detection oceanographic techniques underwater optics Poisson parameter Poisson-Gaussian mixture color correction algorithm expectation maximization approach fish localization illumination problem image preprocessing iterative algorithm mean shift algorithm noise parameters noisy submarine environment optical fish detection optical fish estimation segmentation process standard deviation underwater conditions underwater environment water properties Colored noise Estimation Image color analysis Image segmentation PSNR Underwater vehicles

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