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RECOGNITION OF UNDERWATER TRANSIENT PATTERNS

PATTERN RECOGNITION 1985年第6期18卷 485-490页

作者： CHEN, CH Electrical and Computer Engineering Department Southeastern Massachusetts University North Dartmouth MA 02747 U.S.A

Underwater transients present an unusual but unique recognition problem in that pattern characteristics and categories are not well defined, and the patterns are highly nonstationary. This paper examines the characterization, segmentation and classification of the transient events. A comparison with speech processing and recognition is also made. Although it is difficult to fully characterize the transient data, it is shown that by extracting event portions of the transient waveform through segmentation, a low order autoregressive model can provide an effective feature set for cluster analysis and event classification. Both the segmentation procedure and the recognition experiments with real data are presented in detail.

关键词： Underwater transients segmentation algorithm Autoregressive model Feature extraction Cluster analysis Event classification

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Online path planning of pork cutting robot using 3D laser point cloud

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INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION 2024年第3期51卷 511-517页

作者： Liu, Yi Ning, Rui Du, Mingxin Yu, Shuanghe Yan, Yan Dalian Maritime Univ Coll Marine Elect Engn Dalian Peoples R China

Purpose - The purpose of this paper is to propose an new online path planning method for porcine belly cutting. With the proliferation in demand for the automatic systems of pork production, the development of efficient and robust meat cutting algorithms are hot issues. The uncertain and dynamic nature of the online porcine belly cutting imposes a challenge for the robot to identify and cut efficiently and accurately. Based on the above challenges, an online porcine belly cutting method using 3D laser point cloud is proposed. Design/methodology/approach - The robotic cutting system is composed of an industrial robotic manipulator, customized tools, a laser sensor and a PC. Findings - Analysis of experimental results shows that by comparing with machine vision, laser sensor-based robot cutting has more advantages, and it can handle different carcass sizes. Originality/value - An image pyramid method is used for dimensionality reduction of the 3D laser point cloud. From a detailed analysis of the outward and inward cutting errors, the outward cutting error is the limiting condition for reducing the segments by segmentation algorithm.

关键词： Online cutting path planning Porcine belly cutting 3D laser point cloud Covariance matrix segmentation algorithm

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Multilevel framework to handle object occlusions for real-time tracking

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IET IMAGE PROCESSING 2016年第11期10卷 885-892页

作者： Cai, Yingfeng Wang, Hai Chen, Xiaobo Chen, Long Jiangsu Univ Automot Engn Res Inst Zhenjiang 212013 Peoples R China Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Peoples R China

This study proposes an efficient method to handle the object occlusions seen in monocular traffic image sequences. The motivation of this study is different methods perform differently in occlusion segmentation and the authors' idea is to use a situation-driven approach to aggregate different methods in order to get a good performance. This study classifies occlusion into four categories according to the foreground situation and a multilevel occlusion handling framework is utilised. First, the image segmentation algorithm based on convex hull analysis is utilised for intra-frame level occlusion segmentation. The segmentation algorithm is established by the compactness ratio and interior distance ratio of the foreground. Second, an online sample-based classification algorithm is utilised for tracking level occlusion segmentation. Training samples are extracted from the historical frames before occlusion and testing samples are extracted from the current frame by an adaptive searching strategy. The segmentation of occlusion is transferred into the online classification of testing samples. Such algorithm is established by the similarity and coherence of target's property between continuous frames. Experiments on video sequences illustrate the good performance of the proposed method under different conditions with low computational cost.

关键词： image sequences image segmentation feature extraction object occlusions real-time tracking monocular traffic image sequences multilevel occlusion handling image segmentation convex hull analysis intra-frame level occlusion segmentation segmentation algorithm online sample-based classification algorithm video sequences

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A Novel Fusion Approach to Detect Brain Tumor Using Machine Learning for MRI Images

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TRAITEMENT DU SIGNAL 2022年第4期39卷 1363-1370页

作者： Kaliannan, Srisabarimani Rengaraj, Arthi Daniel, Alex Prabhu SRM Inst Sci & Technol ECE Ramapuram Chennai 600089 Tamil Nadu India Chettinad Hosp & Res Inst Chennai 603103 Tamil Nadu India

Medical Imaging challenges the recent researchers with variability of potential structures, positions and appearance strengths of various tumors present among the patients. The proposed work presents an effective brain tumor watershed segmentation technique created on 2D image followed by statistical feature extraction. Machine Learning models such as SVM, KNN, and XG boost were used to inspire the network design in order to extract tumor existence. The proposed segmentation algorithm has been tested and evaluated on original images that consist of an aggregate of 52 normal MRI volumes of distinctive patients with the presence of tumors or not signifying distinctive structures that obtains outcomes near to physical segmentation implementations. The novelty present in the proposed work classifies whether the tumor is present or not with an accuracy of approximately 98%.

关键词： brain tumor segmentation algorithm XG boost algorithm machine learning

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Expediting adenovirus titer assays via an algorithmic live-cell imaging technique

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JOURNAL OF BIOTECHNOLOGY 2024年 395卷 216-227页

作者： Velikonja, Claire Steenbakkers, Landon How, Joshua Enns, Mackenzie Corbett, Brandon Mccready, Chris Nease, Jake Mhaskar, Prashant Latulippe, David McMaster Univ Dept Chem Engn Hamilton ON Canada Sartorius Canada Inc Oakville ON Canada

Interest in virus-based therapeutics for the treatment of genetic and oncolytic diseases has created a demand for high-yield, low-cost virus-manufacturing processes. However, traditional analytical methods of assessing infectious virus titer require multiple processing steps and manual counting, limiting sample throughput, and increasing human error. This bottleneck severely limits the development of new manufacturing unit operations to drive down costs. In this work, we utilize an Incucyte Live-Cell Analysis System to develop a high-throughput infectious titer assay for adenovirus expressing a GFP-transgene. Although previous studies have demonstrated live-cell imaging's potential for use with other viruses, they provide little guidance regarding the selection of the viewing and analysis parameters. To fill this gap, we develop an algorithmic approach to identify the optimum viewing and analysis parameters and create a statistical workflow for quantifying infectious adenovirus in a sample dilution series in a standard 24-well microplate. The developed assay is comparable to Hexon staining, the gold-standard for adenovirus infectious titer, with a Pearson correlation coefficient of 0.9. Finally, the developed algorithmic approach and statistical workflow were applied to create an assay for adenovirus titer using a 96-well microplate, allowing five times more samples to be quantified compared to the standard 24-well plate. While this assay uses a GFP-insert that precludes its use in a clinical environment, the key learnings surrounding the careful use of viewing and analysis parameters, and the statistical workflow are widely applicable to implementing life-cell imaging for dilution-series-based assays. Moreover, this method directly enables the fast and accurate evaluation of virus samples in a preclinical environment.

关键词： Live-Cell Imaging System Adenovirus Infectious virus titer segmentation algorithm Biotherapeutic manufacturing

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Semiautomatic analysis of phase contrast magnetic resonance imaging of cerebrospinal fluid flow through the aqueduct of Sylvius

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MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2006年第2期19卷 78-87页

作者： Florez, Yudy Natalia Moratal, David Forner, Juana Marti-Bonmati, Luis Arana, Estanislao Guajardo-Hernandez, Ulises Millet-Roig, Jose Resonancia Magnet Serv Radiol Clin Quiron Valencia 46010 Spain Univ Politecn Valencia Grp BET E-46071 Valencia Spain Hosp Univ Dr Peset Valencia Spain

Objective: Quantification of the cerebrospinal fluid (CSF) flow through the aqueduct of Sylvius by means of magnetic resonance imaging (MRI) is subject to interobserver variability due to the region of interest (ROI) selection. Our objective is to develop a semiautomatic measurement method to achieve reproducible quantitative analysis of CSF flow rate and stroke volume. Material and methods: MR examinations were performed using a 1.5 T scanner with a phase contrast sequence (velocity. encoding [V-enc] of 20 cm/s, FOV = 160, 3 mm slice thickness, image matrix size 256 x 256, TR = 53 ms, TE = I I ms, NSA = 2, flip angle = 15 degrees and 23 frames per cardiac cycle with peripheral retrospective pulse gating). Our method was developed using MATLAB R7. Errors introduced by background offset and possible aliased pixels were automatically detected and corrected if necessary in order to calculate the flow parameters that characterize CSF dynamics. The semiautomatic seed method reproducibility was evaluated and compared with the radius method by two observers analysing 21 healthy subjects. Results: The measurements using the semiautomatic seed method reduced the interobservers variability (intra-class correlation [ICC] = 1.0 for stroke volume and for volumetrie flow rate) versus the radius method (ICC = 0.46 for stroke volume and 0.65 for flow rate). Normal stroke volume (39.19 +/- 20.13 mu l/cyele), flow rate (3.81 +/- 2.81 ml/min), maximal mean systolic velocity (5.27 +/- 1.3 cm/s) and maximal mean diastolic velocity (4.20 +/- 1.4 cm/s) were calculated with the half moon and aliasing corrected seed method. Conclusions: Semiautomatic measurements (seed method with half moon background and aliasing correction) allow a generalization of the calculus of flow parameters with great consistency and independency of the operator.

关键词： aliasing correction cerebrospinal fluid magnetic resonance phase imaging segmentation algorithm

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A shifting level model algorithm that identifies aberrations in array-CGH data

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BIOSTATISTICS 2010年第2期11卷 265-280页

作者： Magi, Alberto Benelli, Matteo Marseglia, Giuseppina Nannetti, Genni Scordo, Maria Rosaria Torricelli, Francesca Univ Florence Diagnost Genet Unit Careggi Hosp AOUC I-50141 Florence Italy Univ Florence Ctr Study Complex Dynam I-50019 Florence Italy Univ Florence Dept Med & Surg Crit Care Florence Italy Univ Florence Infantile Neuropsychiat Unit Careggi Hosp AOUC I-50141 Florence Italy

Array comparative genomic hybridization (aCGH) is a microarray technology that allows one to detect and map genomic alterations. The goal of aCGH analysis is to identify the boundaries of the regions where the number of DNA copies changes (breakpoint identification) and then to label each region as loss, neutral, or gain (calling). In this paper, we introduce a new algorithm, based on the shifting level model (SLM), with the aim of locating regions with different means of the log(2) ratio in genomic profiles obtained from aCGH data. We combine the SLM algorithm with the CGHcall calling procedure and compare their performances with 5 state-of-the-art methods. When dealing with synthetic data, our method outperforms the other 5 algorithms in detecting the change in the number of DNA copies in the most challenging situations. For real aCGH data, SLM is able to locate all the cytogenetically mapped aberrations giving a smaller number of false-positive breakpoints than the compared methods. The application of the SLM algorithm is not limited to aCGH data. Our approach can also be used for the analysis of several emerging experimental strategies such as high-resolution tiling array.

关键词： array-CGH segmentation algorithm Shifting level model

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Time and space for segmenting personal photo sets

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MULTIMEDIA TOOLS AND APPLICATIONS 2017年第5期76卷 7141-7173页

作者： Datia, Nuno Pires, Joao Moura Correia, Nuno Inst Politecn Lisboa ISEL Rua Conselheiro Emidio Navarro P-1959007 Lisbon Portugal Univ Nova Lisboa FCT P-2829516 Caparica Portugal

A personal collection of photos shows large variability in the depicted items, making difficult a fully automated solution to cope with sensory and semantic gaps. Emotions and non-visual contextual information can be very important to address those problems. Manual annotations are key, but their time-consuming nature alienate users from doing them. One solution is to lower the annotation effort, building solutions on top of algorithms that prepare a context separation, making possible the reuse of annotations. In this paper we present a segmentation algorithm that uses spatio-temporal information to segment personal photo collections. The algorithm is assessed in a user study, using the participants own photos. The results show users make none or few changes to the proposed segmentations, indicating an acceptance of the algorithm outcome.

关键词： Empirical user study segmentation algorithm Formalisation Personal photo collections

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EUROPHYSICS LETTERS 2003年第2期62卷 189-195页

作者： Fukuda, K Amaral, LAN Stanley, HE Boston Univ Ctr Polymer Studies Boston MA 02215 USA Boston Univ Dept Phys Boston MA 02215 USA NTT Corp Network Innovat Labs Tokyo 1808585 Japan Northwestern Univ Dept Chem Engn Evanston IL 60208 USA

The Internet is a world-wide communication network, whose optimization depends on the knowledge of the statistical characterization of the aggregated traffic flow. Internet traffic is dependent on a number off actors, including communication protocols, network topology, and human behavior. Using a recently proposed segmentation algorithm, we find a surprising analogy between the nonstationarity and the correlations in the communication dynamics in the Internet and in another communication network of great interest: the autonomic nervous system (ANS). The ANS controls involuntary muscle motion, secreting glands, and the heart, hence, we surmise that the time interval between successive heartbeats-an easily measured physiological signal-provides a probe of the communication dynamics for the ANS. We find quantitative similarities between the statistical properties of i) healthy heart rate variability and non-congested Internet traffic, and ii) diseased heart rate variability and congested Internet traffic. Our findings suggest that the understanding of the mechanisms underlying the "human-made" Internet could help to understand the "natural" network that controls the heart.

关键词： .interval ndings communication network time series segmentation algorithm EUROPHYSICS Similarities communication dynamics Internet traffic ANS healthy heart congested

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A PARTICLE segmentation METHOD BASED ON NUCLEATION AND GROWTH OF THE BACKGROUND

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JOURNAL OF MICROSCOPY-OXFORD 1994年第2期173卷 165-172页

作者： ZHENG, X KOLB, M CNRS INST RECH CATALYSEF-69626 VILLEURBANNEFRANCE

A new algorithm for image segmentation is proposed, which is capable of extracting particles in the presence of noise and background fluctuations. It begins with the detection of small regions belonging to the background, called background nuclei, and then lets these nuclei grow to become the entire background. Edge information and region information of the image are used simultaneously.

关键词： ELECTRON MICROSCOPY IMAGE ANALYSIS segmentation algorithm IDENTIFICATION OF PARTICLES

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