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An analysis of the segmentation threshold used in axial-shear strain elastography

ULTRASONICS 2015年第1期55卷 58-64页

作者： Thittai, Arun K. Xia, Rongmin Univ Texas Houston Sch Med Dept Diagnost & Intervent Imaging Ultrason Lab Houston TX USA

Axial-shear strain elastography was introduced recently to image the tumor-host tissue boundary bonding characteristics. The image depicting the axial-shear strain distribution in a tissue under axial compression was termed as an axial-shear strain elastogram (ASSE). It has been demonstrated through simulation, tissue-mimicking phantom experiments, and retrospective analysis of in vivo breast lesion data that metrics quantifying the pattern of axial-shear strain distribution on ASSE can be used as features for identifying the lesion boundary condition as loosely-bonded or firmly-bonded. Consequently, features from ASSE have been shown to have potential in non-invasive breast lesion classification into benign versus malignant. Although there appears to be a broad concurrence in the results reported by different groups, important details pertaining to the appropriate segmentation threshold needed for (1) displaying the ASSE as a color-overlay on top of corresponding Axial Strain Elastogram (ASE) and/or sonogram for feature visualization and (2) ASSE feature extraction are not yet fully addressed. In this study, we utilize ASSE from tissue mimicking phantom (with loosely-bonded and firmly-bonded inclusions) experiments and freehand - acquired in vivo breast lesion data (7 benign and 9 malignant) to analyze the effect of segmentation threshold on ASSE feature value, specifically, the "fill-in" feature that was introduced recently. We varied the segmentation threshold from 20% to 70% (of the maximum ASSE value) for each frame of the acquisition cine-loop of every data and computed the number of ASSE pixels within the lesion that was greater than or equal to this threshold value. If at least 40% of the pixels within the lesion area crossed this segmentation threshold, the ASSE frame was considered to demonstrate a "fill-in" that would indicate a loosely-bonded lesion boundary condition (suggestive of a benign lesion). Otherwise, the ASSE frame was considered not to demons

关键词： Axial-shear strain Benign Elastography Malignant segmentation threshold

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Application of segmentation threshold Method and Wavelet threshold Denoising Based on EMD in Φ-OTDR System 10

Application of Segmentation Threshold Method and Wavelet Thr...

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10th International Conference on Information Optics and Photonics

作者： Ma, Fu Wang, Xiaxiao Liu, Xin Yu, Jia Wang, Tingting Zhang, Wenxia Beihang Univ Sch Instrument Sci & Optoelect Engn 37 Xueyuan Rd Beijing 100191 Peoples R China

ISBN: (纸本)9781510625808

The sensing distance of the traditional phase-sensitive optical time domain reflectometry (Phi-OTDR) distributed optical fiber disturbance sensing system can only reach about 26 km. In order to increase the sensing distance without introducing the new technology and increasing the system cost, a method of processing the data by segmenting thresholds was proposed to increase the system sensing distance to 53.6 km. The locating accuracy is up to 20 m. Considering the impact of noise signal on the system's false alarm problem, a wavelet threshold denoising method based on empirical mode decomposition (EMD) is proposed. Experimental tests show that the method can significantly reduce the noise in the scattering signal and improve the alarm performance of the system.

关键词： phase-sensitive optical time domain reflectometer (Phi-OTDR) segmentation threshold empirical mode decomposition (EMD) wavelet threshold denoising sensing distance

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MTMFNet: multi-threshold and multi-scale feature fusion network for text detection

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VISUAL COMPUTER 2025年 1-16页

作者： Dai, Lei Gao, Wen Tang, Chengyu Wang, Min Chen, Zhihua East China Univ Sci & Technol Dept Comp Sci & Engn Shanghai 200237 Peoples R China

Image feature information is unable to be fully exploited by most existing scene text detection methods, resulting in multi-scale text error detection and crooked text missing detection. This paper focuses on small text detection missing, large text false detection, and low scene text boundary location accuracy caused by multi-scale scene text changes. To overcome these limitations, this paper proposes a text detection method based on multi-threshold and multi-scale feature fusion (MTMFNet). The lightweight network ResNet18 serves as the primary backbone network. Deformable convolution kernels are utilized in feature pyramids to expand the receptive field. Fused attention-oriented mechanism module is introduced to utilize various feature information efficiently and improve the ability of detail feature extraction. Multi-threshold boundary detection module is deployed to generate more accurate text boundaries. This multi-branch structure-based module can sense the cooperative relationship of text boxes using differentiable binarization submodules with associative thresholds. Experimental results indicate that MTMFNet obtains the best comprehensive performance compared with most state-of-the-art text detection methods in terms of four evaluation metrics on three datasets involving the multi-directional text, curved text, and multi-scale text. The related code of our method is available at https://***/Jinfu/MiLNet.

关键词： Scene text detection Attention mechanism segmentation threshold Multi-scale feature fusion

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SAR image segmentation based on analysing similarity with clutter spatial patterns

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ELECTRONICS LETTERS 2016年第21期52卷 1807-1809页

作者： Zhao, Xiaohui Jiang, Yicheng Wang, Wen-Qin Harbin Inst Technol Res Inst Elect Engn Technol Harbin 150001 Heilongjiang Peoples R China Univ Elect Sci & Technol China Sch Commun & Informat Engn Chengdu 611731 Peoples R China

An image segmentation method is proposed based on exploiting the spatial patterns in synthetic aperture radar (SAR) images. First, a similarity map is constructed for evaluating the similarity between the spatial pattern of the SAR image and the reference clutter images. Then, a segmentation threshold is selected based on the similarity map. Finally, image segmentation is achieved by preserving pixels that have larger similarity values. The superiority of the proposed method is verified by the experimental results for high-resolution SAR images.

关键词： synthetic aperture radar radar imaging radar clutter image segmentation image resolution clutter spatial patterns synthetic aperture radar spatial patterns similarity map reference clutter images segmentation threshold similarity values high-resolution SAR images image segmentation method

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A New Regularized Minimum Error thresholding Method

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Transactions of Nanjing University of Aeronautics and Astronautics 2015年第4期32卷 355-364页

作者：王保平张研王晓田吴成茂 National Key Laboratory of Science and Technology on UAV Northwestern Polytechnical University School of Electronics Engineering Xi'an University of Posts and Telecommunications

To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of probability distribution,one proposes the regularized minimum error threshold method and treats the traditional minimum error threshold method as its special *** one constructs the discrete probability distribution by using the separation between segmentation threshold and the average gray-scale values of the object and background of the image so as to compute the information energy of the probability *** impact of the regularized parameter selection on the optimal segmentation threshold of the regularized minimum error threshold method is *** verify the effectiveness of the proposed regularized minimum error threshold method,one selects typical grey-scale images and performs segmentation *** segmentation results obtained by the regularized minimum error threshold method are compared with those obtained with the traditional minimum error threshold *** segmentation results and their analysis show that the regularized minimum error threshold method is feasible and produces more satisfactory segmentation results than the minimum error threshold *** does not exert much impact on object acquisition in case of the addition of a certain noise to an ***,the method can meet the requirements for extracting a real object in the noisy environment.

关键词： image processing image segmentation regularized minimum error threshold method informational divergence segmentation threshold

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Optimization of Flow Imaging Microscopy Setting Using Spherical Beads with Optical Properties Similar to Those of Biopharmaceuticals

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JOURNAL OF PHARMACEUTICAL SCIENCES 2023年第12期112卷 3248-3255页

作者： Kurinomaru, Takaaki Takeda, Kimitoshi Onaka, Megumi Kuruma, Yuki Takahata, Keiji Takahashi, Kayori Sakurai, Hiromu Sasaki, Akira Noda, Naohiro Honda, Shinya Shibuya, Risa Ikeda, Tomohiko Okada, Rio Torisu, Tetsuo Uchiyama, Susumu U Med Inc 2-1 Yamadaoka Suita Osaka 5650871 Japan Osaka Univ Grad Sch Engn Dept Biotechnol 2-1 Yamadaoka Suita Osaka 5650871 Japan Natl Inst Adv Ind Sci & Technol Natl Metrol Inst Japan 1-1-1 Umezono Tsukuba Ibaraki 3058563 Japan Natl Inst Adv Ind Sci & Technol Biomed Res Inst 1-1-1 Higashi Tsukuba Ibaraki 3058566 Japan 2-1 Yamadaoka Suita Osaka 5650871 Japan

Flow imaging microscopy (FIM) is widely used to characterize biopharmaceutical subvisible particles (SVPs). The segmentation threshold, which defines the boundary between the particle and the background based on pixel intensity, should be properly set for accurate SVP quantification. However, segmentation thresholds are often subjectively and empirically set, potentially leading to variations in measurements across instruments and operators. In the present study, we developed an objective method to optimize the FIM segmentation threshold using poly(methyl methacrylate) (PMMA) beads with a refractive index similar to that of biomolecules. Among several candidate particles that were evaluated, 2.5-mu m PMMA beads were the most reliable in size and number, suggesting that the PMMA bead size analyzed by FIM could objectively be used to deter-mine the segmentation threshold for SVP measurements. The PMMA bead concentrations measured by FIM were highly consistent with the indicative concentrations, whereas the PMMA bead size analyzed by FIM decreased with increasing segmentation threshold. The optimal segmentation threshold where the analyzed size was closest to the indicative size differed between an instrument with a black-and-white camera and that with a color camera. Inter-instrument differences in SVP concentrations in acid-stressed recombinant adeno-associated virus (AAV) and protein aggregates were successfully minimized by setting an optimized segmentation threshold specific to the instrument. These results reveal that PMMA beads can aid in determining a more appropriate segmentation threshold to evaluate biopharmaceutical SVPs using FIM.(c) 2023 The Authors. Published by Elsevier Inc. on behalf of American Pharmacists Association. This is an open access article under the CC BY license (http://***/licenses/by/4.0/)

关键词： Biopharmaceutical Flow imaging microscopy Refractive index Subvisible particle segmentation threshold

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Diagnostics of the Structure of Fractal Copper Clusters in a Polytetrafluoroethylene Matrix

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PATTERN RECOGNITION AND IMAGE ANALYSIS 2020年第1期30卷 1-6页

作者： Belko, A., V Babarika, N. N. Zeilikovich, I. S. Nikitin, A., V Grodno State Univ Dept Phys & Technol Grodno 230023 BELARUS

An algorithm for recognizing copper clusters in a polytetrafluoroethylene matrix of a composite material from surface images obtained by optical microscopy is developed. The method is based on threshold cluster segmentation in accordance with the Otsu method. In accordance with the relationship between the square of the perimeter of a fractal object and its area, the fractal dimensions of the filler cluster profiles in the matrix are calculated. The fractal dimensions of the profile of the selected segments of the filler clusters in the polytetrafluoroethylene matrix increase from 1.65 to 1.72 with a change in the mass concentration of copper from 1 to 20%. The filler forms clusters, the structure of which can be described in the modified reaction-limited aggregation (RLA) model. The calculations are performed at the SKIF resource center of the Yanka Kupala State University of Grodno on the IBM FlashSystem 240 cluster supercomputer cluster.

关键词： polymer composites Otsu method segmentation threshold fractal dimension RLA models

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A Method of Color Image Edge Extraction Based on Manhattan Distance Map

A Method of Color Image Edge Extraction Based on Manhattan D...

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9th International Conference on Natural Computation (ICNC)

作者： Jia, Di Fang, Jin-feng He, Xue-ping Meng, Lu Zhang, Yi-fei LiaoNing Tech Univ Sch Elect & Informat Engn Liaoning Peoples R China Northeastern Univ Coll Informat Sci & Engn Liaoning Peoples R China

ISBN: (纸本)9781467347143

Edge extraction is an important topic of image processing, and it is also the basis for subsequent processing. For this reason, this paper proposed a method of color image edge extraction based on Manhattan distance map. Firstly, Manhattan distance map is constructed by adjusting the fuzzy radius and the standard deviation of Gauss nuclear. Edge of the image will be enhanced through the Manhattan distance map, and the gray value of " background" will be reduced. Secondly, Edge of the area is extracted by analysis the gray distribution features of distance map through threshold, and edge region is constructed by the area of edge as foundation. Because the edge region has continuous characteristic, it can be used as the initial distance matrix for GAC model. Finally, edges will be extracted by iterative GAC model in the original image. The results show the method has a better accuracy and practicability.

关键词： Manhattan distance map edge extracting GAC model Gauss template segmentation threshold

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A robustness test of the Braided Device Foreshortening algorithm 13

A robustness test of the Braided Device Foreshortening algor...

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13th International Conference on Medical Information Processing and Analysis

作者： Kale Moyano, Raquel Fernandez, Hector Macho, Juan M. Blasco, Jordi San Roman, Luis Narata, Ana Paula Larrabide, Ignacio Galgo Med SL Barcelona Spain UNICEN CONICET Pladema Tandil Argentina Hosp Clin Prov Barcelona Barcelona Spain Univ Hosp Tours Tours France

ISBN: (数字)9781510616349

ISBN: (纸本)9781510616349

Different computational methods have been recently proposed to simulate the virtual deployment of a braided stent inside a patient vasculature. Those methods are primarily based on the segmentation of the region of interest to obtain the local vessel morphology descriptors. The goal of this work is to evaluate the influence of the segmentation quality on the method named "Braided Device Foreshortening" (BDF). Methods We used the 3DRA images of 10 aneurysmatic patients (cases). The cases were segmented by applying a marching cubes algorithm with a broad range of thresholds in order to generate 10 surface models each. We selected a braided device to apply the BDF algorithm to each surface model. The range of the computed flow diverter lengths for each case was obtained to calculate the variability of the method against the threshold segmentation values. Results. An evaluation study over 10 clinical cases indicates that the final length of the deployed flow diverter in each vessel model is stable, shielding maximum difference of 11.19% in vessel diameter and maximum of 9.14% in the simulated stent length for the threshold values. The average coefficient of variation was found to be 4.08 %. Conclusion A study evaluating how the threshold segmentation affects the simulated length of the deployed FD, was presented. The segmentation algorithm used to segment intracranial aneurysm 3D angiography images presents small variation in the resulting stent simulation.

关键词： Flow Diverter segmentation threshold 3DRA Foreshortening Treatment planning

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An Automatic Image segmentation Algorithm Based on Spiking Neural Network Model

An Automatic Image Segmentation Algorithm Based on Spiking N...

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10th International Conference on Intelligent Computing (ICIC)

作者： Lin, Xianghong Wang, Xiangwen Cui, Wenbo Northwest Normal Univ Sch Comp Sci & Engn Lanzhou 730070 Peoples R China China Telecom Linyi Branch Corp Linyi 276000 Peoples R China

ISBN: (纸本)9783319093338;9783319093321

Inspired by the structure and behavior of the human visual system, an automatic image segmentation algorithm based on a spiking neural network model is proposed. At first, the image pixel values are encoded into the timing of spikes of neurons using the time-to-first-spike coding strategy. Then the segmentation model of spiking neural networks is applied to generate the matrix of spike timing for the visual image. Finally, using the maximum Shannon entropy as the fitness function of genetic algorithm, the evolved segmentation threshold is obtained to segment the visual image. The experimental results show that the method can obtain the optimum segmentation threshold, and achieve satisfactory segmentation results for different images.

关键词： spiking neural network image segmentation genetic algorithm segmentation threshold maximum Shannon entropy

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