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A segmentation algorithm for collision avoidance in telerobotics applications

ROBOTICA 1996年第6期14卷 603-610页

作者： Strenn, S Hsia, TC Wilhelmsen, K UNIV CALIF DAVIS DEPT ECEDAVISCA 95616 LAWRENCE LIVERMORE NATL LAB LIVERMORECA 94550

This paper proposes a new algorithm, known as the segmentation algorithm, which provides model-based, real-time, whole-arm collision avoidance for telerobotic applications. The work presented here is an extension and modification of potential field theory. Novel aspects of the algorithm include the application of a hierarchical segmentation technique to minimize on-line processing and the development of procedures which account for workspace object translation, rotation, and grasping. The SA outputs torques, which, when applied to the control arm, prevent the teleoperator from driving the remote arm into a collision. The teleoperator actually feels workspace objects that are spatially close to the remote arm - an experience known as virtual force-reflection. The SA's performance has been analyzed in terms of its speed and efficiency vis a vis various system parameters, including workspace object distribution, size, and number. Simulation results show that the SA succeeds in providing real-time collision avoidance where less elegant brute force algorithms fail.

关键词： telerobotics collision avoidance segmentation algorithm real-time

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A fast segmentation algorithm for piecewise polynomial numeric function generators

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2011年第14期235卷 4076-4082页

作者： Butler, Jon T. Frenzen, C. L. Macaria, Njuguna Sasao, Tsutomu USN Postgrad Sch Dept Elect & Comp Engn Code EC Bu Monterey CA 93943 USA USN Postgrad Sch Dept Appl Math Monterey CA 93943 USA Kyushu Inst Technol Dept Comp Sci & Elect Iizuka Fukuoka 8208502 Japan

We give an efficient algorithm for partitioning the domain of a numeric function f into segments. The function f is realized as a polynomial in each segment, and a lookup table stores the coefficients of the polynomial. Such an algorithm is an essential part of the design of lookup table methods Ercepovac et al. (2000)[5], Lee et al. (2003)[7], Nagayama et al. (2007) [12], Paul et al. (2007) [6] and Sasao et al. (2004)[8] for realizing numeric functions, such as sin(pi x), In(x), and root-In(x). Our algorithm requires many fewer steps than a previous algorithm given in Frenzen et al. (2010)[10] and makes tractable the design of numeric function generators based on table lookup for high-accuracy applications. We show that an estimate of segment width based on local derivatives greatly reduces the search needed to determine the exact segment width. We apply the new algorithm to a suite of 15 numeric functions and show that the estimates are sufficiently accurate to produce a minimum or near-minimum number of computational steps. Published by Elsevier B.V.

关键词： Numerical approximation Piecewise polynomial approximation Numeric function generators segmentation algorithm Piecewise linear approximation

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Evaluation of water permeability of rough fractures based on a self-affine fractal model and optimized segmentation algorithm

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ADVANCES IN WATER RESOURCES 2019年第Jul.期129卷 99-111页

作者： Ju, Yang Dong, Jiabin Gao, Feng Wang, Jianguo China Univ Min & Technol Beijing State Key Lab Coal Resources & Safe Min D11 Xueyuan Rd Beijing 100083 Peoples R China China Univ Min & Technol State Key Lab Geomech & Deep Underground Engn 1 Univ Ave Xuzhou 221116 Jiangsu Peoples R China

The water permeability of natural fractures is highly related to their morphological characteristics. For fractures with irregular profiles and variable apertures, it is challenging to define an appropriate aperture to apply the traditional cubic law for evaluating permeability. In this study, we propose a novel approach that integrates the standard deviation and the Hurst exponent of a self-affine fracture profile to characterise the effects of fracture morphology on permeability using Cuckoo search algorithms. A modified local cubic law was derived to evaluate permeability, considering the roughness and Hurst exponent of fractures. The required number of segments for a fracture was obtained by comparing simulation results using Lattice Boltzmann methods. The proposed permeability model and segment strategy were validated by experiments on rough fractures. The results show that the number of segments required for the model can be directly derived from the dimensionless aperture (i.e., mechanical aperture/length of fracture media).

关键词： Rough fracture Permeability evaluation Self-affine fractal profile Local cubic law Lattice Boltzmann method segmentation algorithm

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Binary segmentation algorithm for English cursive handwriting recognition

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PATTERN RECOGNITION 2012年第4期45卷 1306-1317页

作者： Lee, Hong Verma, Brijesh Central Queensland University Australia

segmentation in off-line cursive handwriting recognition is a process for extracting individual characters from handwritten words. It is one of the most difficult processes in handwriting recognition because characters are very often connected, slanted and overlapped. Handwritten characters differ in size and shape as well. Hybrid segmentation techniques, especially over-segmentation and validation, are a mainstream to solve the segmentation problem in cursive off-line handwriting recognition. However, the core weakness of the segmentation techniques in the literature is that they impose high risks of chain failure during an ordered validation process. This paper presents a novel Binary segmentation algorithm (BSA) that reduces the risks of the chain failure problems during validation and improves the segmentation accuracy. The binary segmentation algorithm is a hybrid segmentation technique and it consists of over-segmentation and validation modules. The main difference between BSA and other techniques in the literature is that BSA adopts an un-ordered segmentation strategy. The proposed algorithm has been evaluated on CEDAR benchmark database and the results of the experiments are very promising. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Handwriting recognition segmentation algorithm OCR Pattern recognition

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Improving the reproducibility of MR-derived left ventricular volume and function measurements with a semi-automatic threshold-based segmentation algorithm

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INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2013年第3期29卷 617-623页

作者： Jaspers, Karolien Freling, Hendrik G. van Wijk, Kees Romijn, Elisabeth I. Greuter, Marcel J. W. Willems, Tineke P. Univ Groningen Univ Med Ctr Groningen Dept Radiol NL-9700 RB Groningen Netherlands Medis Med Imaging Syst BV NL-2300 AJ Leiden Netherlands Norwegian Univ Sci & Technol Dept Phys NO-7491 Trondheim Norway

To validate a novel semi-automatic segmentation algorithm for MR-derived volume and function measurements by comparing it with the standard method of manual contour tracing. The new algorithms excludes papillary muscles and trabeculae from the blood pool, while the manual approach includes these objects in the blood pool. An epicardial contour served as input for both methods. Multiphase 2D steady-state free precession short axis images were acquired in 12 subjects with normal heart function and in a dynamic anthropomorphic heart phantom on a 1.5T MR system. In the heart phantom, manually and semi-automatically measured cardiac parameters were compared to the true end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF). In the subjects, the semi-automatic method was compared to manual contouring in terms of difference in measured EDV, ESV, EF and myocardial volume (MV). For all measures, intra- and inter-observer agreement was determined. In the heart phantom, EDV and ESV were underestimated for both the semi-automatic. As the papillary muscles were excluded from the blood pool with the semi-automatic method, EDV and ESV were approximately 20 ml lower in the patients, whereas EF was approximately 16 % higher. Intra- and inter-observer agreement was overall improved with the semi-automatic method compared to the manual method. Correlation between manual and semi-automatic measurements was high (EDV: R = 0.99, ESV: R = 0.96;EF: R = 0.80, MV: R = 0.99). The semi-automatic method could exclude endoluminal muscular structures from the blood volume with significantly improved intra- and inter-observer variabilities in cardiac function measurements compared to the conventional, manual method, which includes endoluminal structures in the blood volume.

关键词： Cardiovascular magnetic resonance imaging Left ventricle Function Trabeculae segmentation algorithm

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Global left ventricular function in cardiac CT.: Evaluation of an automated 3D region-growing segmentation algorithm

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EUROPEAN RADIOLOGY 2006年第5期16卷 1117-1123页

作者： Mühlenbruch, G Das, M Hohl, C Wildberger, JE Rinck, D Flohr, TG Koos, R Knackstedt, C Günther, RW Mahnken, AH Rhein Westfal TH Aachen Univ Hosp Dept Diagnost Radiol D-52057 Aachen Germany Siemens Med Solut Forchheim Germany Rhein Westfal TH Aachen Univ Hosp Dept Cardiol D-52057 Aachen Germany

The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16x0.75 mm;120 kV;550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2 +/- 1.0 vs. 2.6 +/- 0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all <= 0.0001);the limits of agreement for the ejection fraction were 2.3 +/- 8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective.

关键词： computed tomography (CT) multislice spiral CT (MSCT) left ventricle cardiac function segmentation algorithm automated segmentation post-processing time time-effectiveness

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The effect of optical degradation from cataract using a new Deep Learning optical coherence tomography segmentation algorithm

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GRAEFES ARCHIVE FOR CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY 2024年第2期262卷 431-440页

作者： Allegrini, Davide Raimondi, Raffaele Sorrentino, Tania Tripepi, Domenico Stradiotto, Elisa Caruso, Marco De Rosa, Francesco Paolo Romano, Mario R. Humanitas Gavazzeni Castelli Eye Ctr Bergamo Italy Humanitas Univ Dept Biomed Sci Via Rita Levi Montalcini 4Pieve Emanuele I-20072 Milan Italy Politecn Torino PolitoBIOMed Lab Biomed Engn Lab I-10129 Turin Italy Politecn Torino Dept Elect & Telecommun I-10129 Turin Italy

PurposeTo assess the validity of the results of a freely available online Deep Learning segmentation tool and its sensitivity to noise introduced by *** OCT images were collected with a Spectralis SD-OCT (Heidelberg Engineering, Heidelberg, Germany) as part of normal clinical practice. Data were segmented using a freely available online tool called Relayer (https://***/), based on a cross-platform Deep Learning segmentation architecture specifically adapted for retinal OCT images. The segmentations were read into MATLAB (The MathWorks, Natick, MA, USA) and *** was an excellent agreement between the ETDRS measurements obtained from the two algorithms. Upon visual inspection, the segmentation based on Deep Learning obtained with Relayer appeared more accurate except in one case of apparent good quality image showing interrupted segmentations in some of the *** freely available online Deep Learning segmentation tool showed good and promising performance in healthy retinas before and after cataract surgery, proving robust to optical degradation of the image from media opacities.

关键词： Optical coherence tomography OCT Cataract optical degradation Deep Learning segmentation algorithm

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Research on Magnetic Resonance Imaging segmentation algorithm

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ENGINEERING LETTERS 2019年第3期27卷 559-567页

作者： Chen, Lin Wei, Dong Wang, Jie-Sheng Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114051 Peoples R China Univ Sci & Technol Liaoning Natl Financial Secur & Syst Equipment Engn Res Ct Anshan Liaoning Peoples R China

Magnetic resonance imaging (MRI) has become an important auxiliary means in the clinical diagnosis of brain diseases and other diseases. The brain images segmentation based on MRI technique mainly includes the segmentation of normal brain tissues and brain images with lesions. The gray-scale distribution of MRI brain images is not uniform because of the noise, migration field effect and partial volume effect in the process of producing the MRI images, and the performance under different image segmentation algorithms is different. The segmentation experiments on single tissue images, MRI brain images and brain abnormal tissue images were carried out based on seven segmentation algorithms (level set, cross entropy, fuzzy entropy, maximum between-class variance, expectation maximization, k-means clustering and fuzzy c-means clustering). The simulation results compared the performance of these seven image segmentation algorithms on the typical MRI brain images.

关键词： Magnetic resonance imaging segmentation algorithm Performance comparison

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segmentation algorithm of Medical Exercise Rehabilitation Image Based on HFCNN and IoT

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IEEE ACCESS 2019年 7卷 160829-160844页

作者： Ding, Liang Ren, Huijie Luliang Univ Dept Phys Educ Luliang 33001 Peoples R China Luliang Univ Inst Fitness & Rehabil Luliang 33001 Peoples R China Dankook Univ Sch Sports Med Cheonan Si 31116 South Korea

Deep learning has achieved great success in the field of computer vision, and the precision in image classification and image detection has surpassed humans. Therefore, this paper combines deep learning and medical image segmentation, focusing on how to improve the accuracy and speed of segmentation algorithm of medical exercise rehabilitation image. Aiming at the shortcomings of traditional medical image recognition methods, a medical exercise rehabilitation image segmentation algorithm based on hierarchical features of convolutional neural networks is proposed, this paper calls it as hierarchical features of convolutional neural networks (HFCNN). The algorithm firstly samples the convolution output of multiple layers in the convolutional neural network to a unified scale and combines them to construct a hierarchical feature. This hierarchical feature combines the structural information of objects contained in the shallow layer of the network with the semantic information of objects contained in the deep layers of the network, so it has a strong ability to express. Secondly, the image can be segmented into multiple super pixels by the super pixel segmentation algorithm. The classifier is trained using the hierarchical features of the super pixel, and then the classification result is mapped back to the pixel. Finally, a fully connected conditional random field algorithm including one-potential potential energy and paired potential energy is constructed. The corresponding energy function is used to smooth the classification result of the pixel, and the regional consistency and continuity of the pixel mark are improved. Compared with many classical convolutional neural network algorithms, this algorithm not only accelerates the network convergence speed, shortens the training time, but also significantly improves the accuracy of segmentation algorithm of medical exercise rehabilitation image, showing good practical value.

关键词： segmentation algorithm IoT medical exercise rehabilitation Image deep learning

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Development of segmentation algorithm for Identifying VOCs (Voice of Customers) with Sales Potential and Those with Negative Attitude at Call Centers 5

Development of Segmentation Algorithm for Identifying VOCs (...

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5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)

作者： Kubota, Ryohei Hu, Xinlong Shobu, Masaki LIXIL Corp Dept Informat Excellence Div Informat Syst Tokyo Japan Keio Univ Grad Sch Business Adm Kanagawa Japan

ISBN: (纸本)9781467389853

VOCs (Voice of Customers) coming through call centers involve a variety of contents such as complaints about products and services, requests for product information and questions about maintenance services, among others. By now, it has been widely recognized that VOCs constitute a valuable source of information for enhancing customer services. Since receiving more than 100,000 VOCs per month is not rare, however, it is virtually impossible to read all of them. Accordingly, it is important to mechanize a procedure for distinguishing VOCs of potential business importance from others, so that valuable information can be extracted from the selected VOCs with speed and cost efficiency. For this purpose, this paper develops a segmentation algorithm for identifying VOCs with Sales Potential and those with Negative Attitude based on a neural network approach combined with text mining.

关键词： call centers VOCs Sales Potential Negative Attitude segmentation algorithm text mining neural network

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