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Journal articles on the topic 'Dice similarity measure'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Afrianda, Cahyapratama, Rossa Sungkono Kelly, and Sarno Riyanarto. "Gap analysis business process model by using structural similarity." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 1 (2020): 124–34. https://doi.org/10.11591/ijeecs.v18.i1.pp124-134.

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Gap analysis process model is a study that can help an institution to determine differences between business process models, such as a model of Standard Operating Procedure and a model of activities in an event log. Gap analysis is used for finding incomplete processes and can be obtained by using structural similarity. Structural similarity measures the similarity of activities and relationships depicting in the models. This research introduces a graph-matching algorithm as the structural similarity algorithm and compares it with dice coefficient algorithms. Graph-matching algorithm notices p

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Albaity, Majed, and Tahir Mahmood. "Medical Diagnosis and Pattern Recognition Based on Generalized Dice Similarity Measures for Managing Intuitionistic Hesitant Fuzzy Information." Mathematics 10, no. 15 (2022): 2815. http://dx.doi.org/10.3390/math10152815.

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Pattern recognition is the computerized identification of shapes, designs, and reliabilities in information. It has applications in information compression, machine learning, statistical information analysis, signal processing, image analysis, information retrieval, bioinformatics, and computer graphics. Similarly, a medical diagnosis is a procedure to illustrate or identify diseases or disorders, which would account for a person’s symptoms and signs. Moreover, to illustrate the relationship between any two pieces of intuitionistic hesitant fuzzy (IHF) information, the theory of generalized di

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Li, Xiaoman, Cui Wang, Xuefu Zhang, and Wei Sun. "Generic SAO Similarity Measure via Extended Sørensen-Dice Index." IEEE Access 8 (2020): 66538–52. http://dx.doi.org/10.1109/access.2020.2984024.

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Kim, Seongho, Ikuko Kato, and Xiang Zhang. "Comparative Analysis of Binary Similarity Measures for Compound Identification in MassSpectrometry-Based Metabolomics." Metabolites 12, no. 8 (2022): 694. http://dx.doi.org/10.3390/metabo12080694.

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Compound identification is a critical step in untargeted metabolomics. Its most important procedure is to calculate the similarity between experimental mass spectra and either predicted mass spectra or mass spectra in a mass spectral library. Unlike the continuous similarity measures, there is no study to assess the performance of binary similarity measures in compound identification, even though the well-known Jaccard similarity measure has been widely used without proper evaluation. The objective of this study is thus to evaluate the performance of binary similarity measures for compound ide

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Cahyapratama, Afrianda, Kelly Rosa Sungkono, and Riyanarto Sarno. "Gap analysis business process model by using structural similarity." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (2020): 124. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp124-134.

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<span>Gap analysis process model is a study that can help an institution to determine differences between business process models, such as a model of Standard Operating Procedure and a model of activities in an event log. Gap analysis is used for finding incomplete processes and can be obtained by using structural similarity. Structural similarity measures the similarity of activities and relationships depicting in the models. This research introduces a graph-matching algorithm as the structural similarity algorithm and compares it with dice coefficient algorithms. Graph-matching algorit

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Mahmood, Tahir, Ubaid Ur Rehman, Zeeshan Ali, and Ronnason Chinram. "Jaccard and Dice Similarity Measures Based on Novel Complex Dual Hesitant Fuzzy Sets and Their Applications." Mathematical Problems in Engineering 2020 (November 11, 2020): 1–25. http://dx.doi.org/10.1155/2020/5920432.

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Complex dual hesitant fuzzy set (CDHFS) is a combination of two modifications, called complex fuzzy set (CFS) and dual hesitant fuzzy set (DHFS). CDHFS makes two degrees, called membership valued and nonmembership valued in the form of a finite subset of a unit disc in the complex plane, and is a capable method to solve uncertain and unpredictable information in real-life problems. The goal of this study is to describe the notion of CDHFS and its operational laws. The novel approach of the complex interval-valued dual hesitant fuzzy set (CIvDHFS) and its fundamental laws are also described and

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Ren, Shapu. "Multicriteria Decision-Making Method Under a Single Valued Neutrosophic Environment." International Journal of Intelligent Information Technologies 13, no. 4 (2017): 23–37. http://dx.doi.org/10.4018/ijiit.2017100102.

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A single valued neutrosophic set (SVNS) is a subclass of neutrosophic sets, which generalizes fuzzy sets, interval valued fuzzy set, and intuitionistic fuzzy set. It can be used to easily express incomplete, indeterminate and inconsistent information. This paper introduces the Dice similarity measure of single valued neutrosophic numbers (SVNNs) for ranking SVNNs and a single valued neutrosophic prioritized weighted geometric (SVNPWG) operator for aggregating single valued neutrosophic information. Based on the SVNPWG operator and the Dice similarity measure for SVNNs, a multicriteria decision

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Tiwari, Sunita, and Saroj Kaushik. "EMD-Based Semantic User Similarity Using Past Travel Histories." Journal of Cases on Information Technology 24, no. 3 (2022): 1–17. http://dx.doi.org/10.4018/jcit.20220701.oa2.

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The cost-effective and easy availability of handheld mobile devices and ubiquity of location acquisition services such as GPS and GSM networks has helped expedient logging and sharing of location histories of mobile users. This work aims to find semantic user similarity using their past travel histories. Application of the semantic similarity measure can be found in tourism-related recommender systems and information retrieval. The paper presents Earth Mover’s Distance (EMD) based semantic user similarity measure using users' GPS logs. The similarity measure is applied and evaluated on the GPS

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Sulaiman, Nor Hashimah, Daud Mohamad, Jamilah Mohd Shariff, Sharifah Aniza Sayed Ahmad, and Kamilah Abdullah. "Extended FTOPSIS with Distance and Set Theoretic-Based Similarity Measure." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 2 (2018): 387. http://dx.doi.org/10.11591/ijeecs.v9.i2.pp387-394.

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Comparing fuzzy numbers is an essential process in deducing the output of many fuzzy decision making methods. One of the comparison methods commonly used is by using similarity measure. The main advantage of the similarity measure over other approaches is its ability to minimize the loss of information in the computational process. Several similarity measures have been applied effectively in fuzzy decision making methods. In this paper, a new similarity measure based on the geometric distance, the center of gravity, Hausdorf distance and the set theoretic similarity formula known as the Dice s

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Extended, FTOPSIS with Distance and Set Theoretic-Based Similarity Measure, Mohamad Daud, Mohd Shariff Jamilah, Aniza Sayed Ahmad Sharifah, and Abdullah Kamilah. "Extended FTOPSIS with Distance and Set Theoretic-Based Similarity Measure." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 2 (2018): 387–94. https://doi.org/10.11591/ijeecs.v9.i2.pp387-394.

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Comparing fuzzy numbers is an essential process in deducing the output of many fuzzy decision making methods. One of the comparison methods commonly used is by using similarity measure. The main advantage of the similarity measure over other approaches is its ability to minimize the loss of information in the computational process. Several similarity measures have been applied effectively in fuzzy decision making methods. In this paper, a new similarity measure based on the geometric distance, the center of gravity, Hausdorf distance and the set theoretic similarity formula known as the Dice s

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Yi-Ting Huang, Yi-Ting Huang, Wan-Hui Lee Yi-Ting Huang, and Jen-Hui Tsai Wan-Hui Lee. "A New Approach to Multiple Criteria Decision-Making Using the Dice Similarity Measure under Fermatean Fuzzy Environments." 網際網路技術學刊 24, no. 4 (2023): 849–60. http://dx.doi.org/10.53106/160792642023072404003.

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<p>Many contemporary multiple criteria decision-making (MCDM) problems are rather complicated and uncertain to manage. MCDM problems can be complex because they involve making decisions based on multiple conflicting criteria, and they can be uncertain because they often involve incomplete or subjective information. This can make it difficult to determine the optimal solution to the problem. Over the last decades, tens of thousands MCDM methods have been proposed based on fuzzy sets (FSs) and intuitionistic fuzzy sets (IFSs). In this paper, we propose a new MCDM method based on Fermatean

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Sakira Kamaruddin, Siti, Yuhanis Yusof, Nur Azzah Abu Bakar, Mohamed Ahmed Tayie, and Ghaith Abdulsattar A.Jabbar Alkubaisi. "Graph-based Representation for Sentence Similarity Measure : A Comparative Analysis." International Journal of Engineering & Technology 7, no. 2.14 (2018): 32. http://dx.doi.org/10.14419/ijet.v7i2.14.11149.

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Textual data are a rich source of knowledge; hence, sentence comparison has become one of the important tasks in text mining related works. Most previous work in text comparison are performed at document level, research suggest that comparing sentence level text is a non-trivial problem. One of the reason is two sentences can convey the same meaning with totally dissimilar words. This paper presents the results of a comparative analysis on three representation schemes i.e. term frequency inverse document frequency, Latent Semantic Analysis and Graph based representation using three similarity

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Anantharajan, Shenbagarajan, Shenbagalakshmi Gunasekaran, and havasi Subramanian. "Brain Tumor Segmentation based on Red-Bellied Woodpecker Mating Optimization Algorithm." NeuroQuantology 20, no. 5 (2022): 785–90. http://dx.doi.org/10.14704/nq.2022.20.5.nq22235.

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Earlier, many researchers proposed various segmentation algorithms to segment tumor from MRI Brain image. The method of a nature-inspired meta heuristic-based woodpecker characteristics approach is used to segment the tumored area of this proposed study. In this automated MRI brain tumor segmentation, the MRI brain image gets enhanced for improving the performance of the segmentation accompanied by the skull elimination phase to eliminate the morphological operations of all non-brain tissues. In the end, the RBWMOA (Red-Bellied Woodpecker Mating Optimization Algorithm) is suggested for the seg

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Febriansyah, Luke Michael, and Shinta Estri Wahyuningrum. "ANALYSIS WINNOWING ALGORITHM FOR TEXT PLAGIARISM DETECTION USING THREE METHOD SIMILARITY." Proxies : Jurnal Informatika 2, no. 2 (2021): 42. http://dx.doi.org/10.24167/proxies.v2i2.3208.

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Cases of plagiarism in recent years has been an issues. Based on that issues, this research will create a system to detect similarity in a text. There is an aspect as reference of the research that is analyze the plagiarism algorithm. This research will analyze the accuracy one of plagiarism check algorithm, winnowing algorithm. Winnowing algorithm is a plagiarism detection algorithm based on document fingerprinting. To calculate percentage similarity of document fingerprinting in text, there are 3 methods to measure similarity that will be used in this research, which is jaccard similarity co

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Ali, Muhammad Haidar, and Faisal Rahutomo. "MANHATTAN DISTANCE AND DICE SIMILARITY EVALUATION ON INDONESIAN ESSAY EXAMINATION SYSTEM." JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 4, no. 2 (2019): 156. http://dx.doi.org/10.29100/jipi.v4i2.1398.

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<span lang="EN-US">Each learning process requires an evaluation tool to measure the level of understanding of students. The type of evaluation can be multiple choice questions, short entries and essays. Some studies reveal essay exams better than other types of evaluations. An essay assessment is automatically needed to save teacher time in correcting answers. However, the development of essay assessments is still ongoing. The aim is to obtain a better accuracy value than the method used in the assessment. Based on these problems, this study proposes a comparative analysis of similarity

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Singh, Akanksha, and Sanjay Kumar. "A novel dice similarity measure for IFSs and its applications in pattern and face recognition." Expert Systems with Applications 149 (July 2020): 113245. http://dx.doi.org/10.1016/j.eswa.2020.113245.

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17

Setiawan, Rudi. "Similarity Checking Similarity Checking of Source Code Module Using Running Karp Rabin Greedy String Tiling." Science Proceedings Series 1, no. 2 (2019): 43–46. http://dx.doi.org/10.31580/sps.v1i2.624.

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   Similarity checking of source code module, required a long process if it is done manually. Based on that problem, this research designed a software with structure-based approach using string matching technique with Running Karp-Rabin Greedy String Tiling (RKR-GST) Algorithm to check the similarity and using Dice Coefficient method to measure the level of similarity from 2 results source code modules.    The result of the experiments show that RKRGST which applied in this system capable of recognizing the changing of statement and the changing statem

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18

Ye, Jun. "Multicriteria decision-making method using the Dice similarity measure between expected intervals of trapezoidal fuzzy numbers." Journal of Decision Systems 21, no. 4 (2012): 307–17. http://dx.doi.org/10.1080/12460125.2012.734265.

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19

Dutta, Palash. "An advanced dice similarity measure of generalized fuzzy numbers and its application in multicriteria decision making." Arab Journal of Basic and Applied Sciences 27, no. 1 (2020): 75–92. http://dx.doi.org/10.1080/25765299.2020.1724012.

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20

Alias, Suriana, Daud Mohamad, Adibah Shuib, et al. "Rough Neutrosophic Multisets Geometric Aggregation Operator with Entropy Weight Combined Roughness Dice Similarity Measure and Its Application." ITM Web of Conferences 67 (2024): 01026. http://dx.doi.org/10.1051/itmconf/20246701026.

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Rough neutrosophic multisets (RNM) is an uncertainty set theory generalized from the rough neutrosophic set. In the same equivalence relation, the universal set is a neutrosophic multisets with boundary regions involving lower and upper approximation. To date, to handle the multiplicity of information collected, the rough neutrosophic multisets geometric aggregation operator (RNMGAO) is introduced. The algebraic operations of RNM used in the derivation of RNMGAO are defined. The entropy measure of RNM is also discussed as a weighted assign for each criterion simultaneously with the geometric a

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Simanjuntak, Ruth Rani, A. M. H. Pardede, and Zira Fatmaira. "Application of the KARP RABIN Algorithm for Plagiarism Detection System in Thesis Proposal Submission in the Department of Informatics Engineering STMIK Kaputama." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 1 (2024): 396–403. http://dx.doi.org/10.59934/jaiea.v4i1.644.

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Plagiarism is a serious threat, especially to academic honesty, so a detection system that can analyze various types of documents is needed. This research develops a plagiarism detection system using Optical Character Recognition (OCR) to convert image text into digital text. Rabin – Karp algorithm with rolling hash and Dice Coefficient Similarity is applied to measure similarities between documents. Testing is carried out on .doc, .txt, .jpg files. As a result, the system can detect plagiarism well in clear text and image documents, but accuracy can decrease in low-quality images. In conclusi

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Tuan, Tran Manh, Luong Thi Hong Lan, Shuo-Yan Chou, et al. "M-CFIS-R: Mamdani Complex Fuzzy Inference System with Rule Reduction Using Complex Fuzzy Measures in Granular Computing." Mathematics 8, no. 5 (2020): 707. http://dx.doi.org/10.3390/math8050707.

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Complex fuzzy theory has strong practical background in many important applications, especially in decision-making support systems. Recently, the Mamdani Complex Fuzzy Inference System (M-CFIS) has been introduced as an effective tool for handling events that are not restricted to only values of a given time point but also include all values within certain time intervals (i.e., the phase term). In such decision-making problems, the complex fuzzy theory allows us to observe both the amplitude and phase values of an event, thus resulting in better performance. However, one of the limitations of

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Mayo, Kathryn, Stefano Pretolani, Giovanni Gasbarrini, Giancarlo Ghironzi, and Francis Megraud. "Heterogeneity of Immunoglobulin G Response toHelicobacter pylori Measured by the Unweighted Pair Group Method with Averages." Clinical Diagnostic Laboratory Immunology 5, no. 1 (1998): 70–73. http://dx.doi.org/10.1128/cdli.5.1.70-73.1998.

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ABSTRACT The heterogeneity of the immune response to Helicobacter pylori has always been noticed but has never been evaluated by obtaining a quantitative measure. For this purpose, sera were tested by enzyme-linked immunosorbent assay, and 207 positive serum specimens were subsequently tested by immunoblotting. The presence or absence of six specific bands was noted. The homology of the different profiles of bands was measured by calculating the Dice coefficient, and a dendrogram was constructed. Thirty-four profiles were found, with each profile containing from 1 to 43 serum specimens. At a l

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Kang, Yena Christina, Hee Kyung Yang, Young Jae Kim, Jeong-Min Hwang, and Kwang Gi Kim. "Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions." BioMed Research International 2022 (March 24, 2022): 1–7. http://dx.doi.org/10.1155/2022/9840494.

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This study presents an automated algorithm that measures ocular deviation quantitatively using photographs of the nine cardinal points of gaze by means of deep learning (DL) and image processing techniques. Photographs were collected from patients with strabismus. The images were used as inputs for the DL segmentation models that segmented the sclerae and limbi. Subsequently, the images were registered for the mathematical algorithm. Two-dimensional sclera and limbus were modeled, and the corneal light reflex points of the primary gaze images were determined. Limbus recognition was performed t

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Muhadi, Nur, Ahmad Abdullah, Siti Bejo, Muhammad Mahadi, and Ana Mijic. "Image Segmentation Methods for Flood Monitoring System." Water 12, no. 6 (2020): 1825. http://dx.doi.org/10.3390/w12061825.

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Flood disasters are considered annual disasters in Malaysia due to their consistent occurrence. They are among the most dangerous disasters in the country. Lack of data during flood events is the main constraint to improving flood monitoring systems. With the rapid development of information technology, flood monitoring systems using a computer vision approach have gained attention over the last decade. Computer vision requires an image segmentation technique to understand the content of the image and to facilitate analysis. Various segmentation algorithms have been developed to improve result

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Sheela, S. "Enhancer for ovarian cyst segmentation using adaptive thresholding technique." Indian Journal of Science and Technology 13, no. 39 (2020): 4142–50. http://dx.doi.org/10.17485/ijst/v13i39.1602.

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Objective: To achieve the accurate segmentation of ovarian cyst from the ultrasound images. Method: Ovarian cyst ultrasound images are taken from ultrasound images.com and sonoworld.com. The cysts are segmented using adaptive thresholding technique. The segmented image (binary image) is divided into sub blocks and then number of binary transition in each block is calculated. Based on the number of transition, the pixel values are replaced by 0 or the same pixel value is maintained. In order to measure the performance of the proposed enhancer various measures like Accuracy (ACC), Dice Coefficie

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LYRAS, DIMITRIOS P., KYRIAKOS N. SGARBAS, and NIKOLAOS D. FAKOTAKIS. "APPLYING SIMILARITY MEASURES FOR AUTOMATIC LEMMATIZATION: A CASE STUDY FOR MODERN GREEK AND ENGLISH." International Journal on Artificial Intelligence Tools 17, no. 05 (2008): 1043–64. http://dx.doi.org/10.1142/s021821300800428x.

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This paper addresses the problem of automatic induction of the normalized form (lemma) of regular and mildly irregular words with no direct supervision using language-independent algorithms. More specifically, two string distance metric models (i.e. the Levenshtein Edit Distance algorithm and the Dice Coefficient similarity measure) were employed in order to deal with the automatic word lemmatization task by combining two alignment models based on the string similarity and the most frequent inflectional suffixes. The performance of the proposed model has been evaluated quantitatively and quali

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Duan, Xiaoyu, Huiyan Jiang, and Siqi Li. "Shape and Boundary Similarity Features for Accurate HCC Image Recognition." BioMed Research International 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/3764576.

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Nucleus morphology is of great importance in conventional cancer pathological diagnosis, which could provide information difference between normal and abnormal nuclei visually. Therefore, this paper proposes two novel kinds of features for normal and hepatocellular carcinoma (HCC) nucleus recognition, including shape and boundary similarity. First, each individual nucleus patch with the fixed size is obtained using center-proliferation segmentation (CPS) method. Then, nucleus shape library is constructed based on manual selection by pathologists, which is utilized to measure nucleus shape simi

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Ibrahim, Arsmah, Zainab Abu Bakar, Nuru’l–‘Izzah Othman, and Nor Fuzaina Ismail. "Assessing the Line-By-Line Marking Performance of n-Gram String Similarity Method." Scientific Research Journal 6, no. 1 (2009): 15. http://dx.doi.org/10.24191/srj.v6i1.5636.

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Manual marking of free-response solutions in mathematics assessments is very demanding in terms of time and effort. Available software equipped with automated marking features to mark open-ended questions has very limited capabilities. In most cases the marking process focuses on the final answer only. Few available software are capable of marking the intermediate steps as is norm in manual marking. This paper discusses the line-by-line marking performance of the n_gram string similarity method using the Dice coefficient as means to measure similarity. The marks awarded by the automated markin

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Montazerolghaem, Maryam, Yu Sun, Giuseppe Sasso, and Annette Haworth. "U-Net Architecture for Prostate Segmentation: The Impact of Loss Function on System Performance." Bioengineering 10, no. 4 (2023): 412. http://dx.doi.org/10.3390/bioengineering10040412.

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Segmentation of the prostate gland from magnetic resonance images is rapidly becoming a standard of care in prostate cancer radiotherapy treatment planning. Automating this process has the potential to improve accuracy and efficiency. However, the performance and accuracy of deep learning models varies depending on the design and optimal tuning of the hyper-parameters. In this study, we examine the effect of loss functions on the performance of deep-learning-based prostate segmentation models. A U-Net model for prostate segmentation using T2-weighted images from a local dataset was trained and

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Goyal, Ayush, Sunayana Tirumalasetty, Gahangir Hossain, et al. "Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images." Journal of Healthcare Engineering 2019 (February 14, 2019): 1–21. http://dx.doi.org/10.1155/2019/9610212.

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This research presents an independent stand-alone graphical computational tool which functions as a neurological disease prediction framework for diagnosis of neurological disorders to assist neurologists or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images. The tool was built in collaboration with neurologists and neurosurgeons and many of the features are based on their feedback. This tool provides the user automatized functionality to perform automatic segmentation and extract the gray and white matter regions of patient brain im

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Dey, Paramita, Subhayan Bhattacharya, and Sarbani Roy. "A Survey on the Role of Centrality as Seed Nodes for Information Propagation in Large Scale Network." ACM/IMS Transactions on Data Science 2, no. 3 (2021): 1–25. http://dx.doi.org/10.1145/3465374.

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From the popular concept of six-degree separation, social networks are generally analyzed in the perspective of small world networks where centrality of nodes play a pivotal role in information propagation. However, working with a large dataset of a scale-free network (which follows power law) may be different due to the nature of the social graph. Moreover, the derivation of centrality may be difficult due to the computational complexity of identifying centrality measures. This study provides a comprehensive and extensive review and comparison of seven centrality measures (clustering coeffici

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Deng, Liwei, Shanshan Liu, Xiaofei Wang, Guofu Zhao, and Jiazhong Xu. "Particle Swarm Optimization and Salp Swarm Algorithm for the Segmentation of Diabetic Retinal Blood Vessel Images." Computational Intelligence and Neuroscience 2022 (August 23, 2022): 1–14. http://dx.doi.org/10.1155/2022/1936482.

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In recent years, the incidence of diabetes has been increasing year by year. Since most of the fundus lesions are located near blood vessels, the image information is complex, and the end vessels are difficult to identify. So, a new segmentation method of diabetic retinal vessel images based on particle swarm optimization and salp swarm algorithm is proposed. This paper uses a Gaussian filter to enhance the main blood vessels, and a top-bot hat transform is used to strengthen the end vessels. The preprocessing process is completed by combining and reconstructing the two images through a normal

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Nurhuda Ismail, Abdul Kadir Jumaat, and Nurul Fatin Azara Zulkarnain. "An Improved Variational-Based Model for Denoising and Segmentation of Vector-Valued Images." Journal of Advanced Research in Applied Sciences and Engineering Technology 40, no. 1 (2024): 189–203. http://dx.doi.org/10.37934/araset.40.1.189203.

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Preserving important features such as edges is one of the main concerns in models for denoising and segmenting vector-valued (colour) images. The Rudin-Osher-Fatemi (ROF) model is a well-known variational-based image denoising model that is capable of reducing image noise while preserving image edges. However, the ROF model is not formulated for denoising colour images and is less effective in preserving corners and weak edges. On the other hand, a variational-based selective segmentation model for colour images called the selective distance segmentation (DSS2) model has recently been proposed

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Muhammad Nazim, Nor’ Awatif Amri, Normi Abdul Hadi, Mohd Rijal Ilias, Dian Kurniasari, and Suhaila Abd Halim. "Application of Different Distance Metrics on K-Means Clustering Algorithm for Retinal Vessel Images." Semarak International Journal of Machine Learning 4, no. 1 (2025): 14–26. https://doi.org/10.37934/sijml.4.1.1426a.

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Accurate segmentation of retinal blood vessels is important for the early detection and treatment of a variety of ocular disorders, including diabetic retinopathy and glaucoma. There are various methods used in image segmentation and one of them is K-means clustering. The problems of K-means clustering are its initial cluster centres, the spherical clusters’ assumption, and the hard assignment of the pixels to the clusters, which has led to the improvements of the algorithm. These problems are closely related to the choice of distance metrics. In this study, the following objectives have been

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Muhammad Nazim, Nor’ Awatif Amri, Normi Abdul Hadi, Mohd Rijal Ilias, Dian Kurniasari, and Suhaila Abd Halim. "Application of Different Distance Metrics on K-Means Clustering Algorithm for Retinal Vessel Images." Semarak International Journal of Machine Learning 4, no. 1 (2024): 14–26. https://doi.org/10.37934/sijml.4.1.1426.

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Accurate segmentation of retinal blood vessels is important for the early detection and treatment of a variety of ocular disorders, including diabetic retinopathy and glaucoma. There are various methods used in image segmentation and one of them is K-means clustering. The problems of K-means clustering are its initial cluster centres, the spherical clusters’ assumption, and the hard assignment of the pixels to the clusters, which has led to the improvements of the algorithm. These problems are closely related to the choice of distance metrics. In this study, the following objectives have been

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Huddin, Azzam Basseri, Aqilah Baseri Huddin, Anas Tharek, Wan Mimi Diyana Wan Zaki, and Ahmad Sobri Muda. "Evaluation of Intracerebral Haemorrhage’s Surface Area Using Artificial Intelligence in Computed Tomography." Journal Of Cardiovascular, Neurovascular & Stroke 4, no. 3 (2022): 1–13. http://dx.doi.org/10.32896/cvns.v4n3.1-13.

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Introduction: AI-based techniques can be used to localize and measure the intracerebral haemorrhage (ICH) in computed tomography (CT). This study aims to develop an automated detection algorithm with higher sensitivity in ICH evaluation in comparison to the conventional method. This indirectly influences the patient’s prognosis by reducing the risk of delay or misdiagnosis. Methods: Selected 50 CT brain images with primary ICH were used for three different measurement approaches including the conventional Kothari method (Conventional), AI-based method (A.I.), and manually marking by the radiol

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Aruchsamy, Revathy, Inthumathi Velusamy, Prasantha Bharathi Dhandapani, Suleman Nasiru, and Christophe Chesneau. "Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications." Journal of Mathematics 2024 (May 7, 2024): 1–21. http://dx.doi.org/10.1155/2024/6503747.

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The circular Fermatean fuzzy (CFF) set is an advancement of the Fermatean fuzzy (FF) set and the interval-valued Fermatean fuzzy (IVFF) set which deals with uncertainty. The CFF set is represented as a circle of radius ranging from 0 to 2 with the center at the degree of association (DA) and degree of nonassociation (DNA). If multiple people are involved in making decisions, the CFF set, as an alternative to the FF and IVFF sets, can deal with ambiguity more effectively by encircling the decision values within a circle rather than taking an average. Using algorithms, a pattern can be observed

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S, Sheela, and Sumathi M. "Enhancer for ovarian cyst segmentation using adaptive thresholding technique." Indian Journal of Science and Technology 13, no. 39 (2020): 4142–50. https://doi.org/10.17485/IJST/v13i39.1602.

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Abstract <strong>Objective:</strong> To achieve the accurate segmentation of ovarian cyst from the ultrasound images. <strong>Method:</strong> Ovarian cyst ultrasound images are taken from ultrasound images.com and sonoworld.com. The cysts are segmented using adaptive thresholding technique. The segmented image (binary image) is divided into sub blocks and then number of binary transition in each block is calculated. Based on the number of transition, the pixel values are replaced by 0 or the same pixel value is maintained. In order to measure the performance of the proposed enh

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Apivanichkul, Kamonchat, Pattarapong Phasukkit, Pittaya Dankulchai, Wiwatchai Sittiwong, and Tanun Jitwatcharakomol. "Enhanced Deep-Learning-Based Automatic Left-Femur Segmentation Scheme with Attribute Augmentation." Sensors 23, no. 12 (2023): 5720. http://dx.doi.org/10.3390/s23125720.

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This research proposes augmenting cropped computed tomography (CT) slices with data attributes to enhance the performance of a deep-learning-based automatic left-femur segmentation scheme. The data attribute is the lying position for the left-femur model. In the study, the deep-learning-based automatic left-femur segmentation scheme was trained, validated, and tested using eight categories of CT input datasets for the left femur (F-I–F-VIII). The segmentation performance was assessed by Dice similarity coefficient (DSC) and intersection over union (IoU); and the similarity between the predicte

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Choi, Woorim, Chul-Ho Kim, Hyein Yoo, Hee Rim Yun, Da-Wit Kim, and Ji Wan Kim. "Development and validation of a reliable method for automated measurements of psoas muscle volume in CT scans using deep learning-based segmentation: a cross-sectional study." BMJ Open 14, no. 5 (2024): e079417. http://dx.doi.org/10.1136/bmjopen-2023-079417.

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ObjectivesWe aimed to develop an automated method for measuring the volume of the psoas muscle using CT to aid sarcopenia research efficiently.MethodsWe used a data set comprising the CT scans of 520 participants who underwent health check-ups at a health promotion centre. We developed a psoas muscle segmentation model using deep learning in a three-step process based on the nnU-Net method. The automated segmentation method was evaluated for accuracy, reliability, and time required for the measurement.ResultsThe Dice similarity coefficient was used to compare the manual segmentation with autom

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Sun, Lingtong, Juan Chen, Li Jun Li, and Lingdi Li. "Similarity-based metric analysis approach for predicting osteogenic differentiation correlation coefficients and discovering the novel osteogenic-related gene FOXA1 in BMSCs." PeerJ 12 (September 19, 2024): e18068. http://dx.doi.org/10.7717/peerj.18068.

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Background As a powerful tool, bioinformatics analysis is playing an increasingly important role in many fields. Osteogenic differentiation is a complex biological process involving the fine regulation of numerous genes and signaling pathways. Method Osteogenic differentiation-related genes are collected from the online databases. Then, we proposed two indexes Jaccard similarity and Sorensen-Dice similarity to measure the topological relevance of genes in the human PPI network. Furthermore, we selected three pathways involving osteoblast-related transcription factors, osteoblast differentiatio

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DAVIS, M. A., D. D. HANCOCK, T. E. BESSER, et al. "Correlation between geographic distance and genetic similarity in an international collection of bovine faecal Escherichia coli O157[ratio ]H7 isolates." Epidemiology and Infection 131, no. 2 (2003): 923–30. http://dx.doi.org/10.1017/s0950268803008884.

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Evidence from epidemiological and molecular studies of bovine Escherichia coli O157[ratio ]H7 suggests that strains are frequently transmitted across wide geographic distances. To test this hypothesis, we compared the geographic and genetic distance of a set of international bovine Escherichia coli O157[ratio ]H7 isolates using the Mantel correlation. For a measure of genetic relatedness, pulsed-field gel electrophoresis of six different restriction enzyme digests was used to generate an average Dice similarity coefficient for each isolate pair. Geographic distance was calculated using latitud

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Jeganathan, Thibaut, Emile Salgues, Ulrike Schick, et al. "Inter-Rater Variability of Prostate Lesion Segmentation on Multiparametric Prostate MRI." Biomedicines 11, no. 12 (2023): 3309. http://dx.doi.org/10.3390/biomedicines11123309.

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Introduction: External radiotherapy is a major treatment for localized prostate cancer (PCa). Dose escalation to the whole prostate gland increases biochemical relapse-free survival but also acute and late toxicities. Dose escalation to the dominant index lesion (DIL) only is of growing interest. It requires a robust delineation of the DIL. In this context, we aimed to evaluate the inter-observer variability of DIL delineation. Material and Methods: Two junior radiologists and a senior radiation oncologist delineated DILs on 64 mpMRIs of patients with histologically confirmed PCa. For each mpM

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Ye, Jun. "The Dice similarity measure between generalized trapezoidal fuzzy numbers based on the expected interval and its multicriteria group decision-making method." Journal of the Chinese Institute of Industrial Engineers 29, no. 6 (2012): 375–82. http://dx.doi.org/10.1080/10170669.2012.710879.

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Piccolo, Lidia Del, Maria Grazia Benpensanti, Piero Bonini, Paola Cellerino, Anna Saltini, and Christa Zimmermann. "The Verona-Medical Interview Classification System/Patient (VR-MICS/P). The instrument and its reliability." Epidemiologia e Psichiatria Sociale 8, no. 1 (1999): 56–67. http://dx.doi.org/10.1017/s1121189x00007521.

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SummaryObjective – To assess the reliability and to describe the categories and the procedure to apply the VRMICS/P (Verona-Medical Interview Classification System/Patient). Setting – The interviews used for the reliability study were audio taped. Five general practitioners (GPs) working in two general practices in South-Verona recorded their consultations. Sample – 50 interviews selected randomly from 120, 10 for each GP. The selection criterion for the participating patients was a GHQ-12 score of 3 and the consultation for a new illness episode. Main outcome measures -The VR-MICS/P classifie

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Mystica, A. R., and M. M. M. Merlin. "AN EXTENDED TOPSIS METHOD BASED ON GENERALIZED WEIGHTED DICE SIMILARITY MEASURE AND INTUITIONISTIC PREFERENCE RELATION WITH INTUITIONISTIC FUZZY MULTI ATTRIBUTE DECISION MAKING." Advances in Mathematics: Scientific Journal 9, no. 4 (2020): 1835–44. http://dx.doi.org/10.37418/amsj.9.4.40.

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Ye, Jun. "Multicriteria decision-making method using the Dice similarity measure based on the reduct intuitionistic fuzzy sets of interval-valued intuitionistic fuzzy sets." Applied Mathematical Modelling 36, no. 9 (2012): 4466–72. http://dx.doi.org/10.1016/j.apm.2011.11.075.

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Khagi, Bijen, and Goo-Rak Kwon. "Pixel-Label-Based Segmentation of Cross-Sectional Brain MRI Using Simplified SegNet Architecture-Based CNN." Journal of Healthcare Engineering 2018 (October 28, 2018): 1–8. http://dx.doi.org/10.1155/2018/3640705.

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Using deep neural networks for segmenting an MRI image of heterogeneously distributed pixels into a specific class assigning a label to each pixel is the concept of the proposed approach. This approach facilitates the application of the segmentation process on a preprocessed MRI image, with a trained network to be utilized for other test images. As labels are considered expensive assets in supervised training, fewer training images and training labels are used to obtain optimal accuracy. To validate the performance of the proposed approach, an experiment is conducted on other test images (avai

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Selçuk, Turab. "The Development of a Yolov8-Based Model for the Measurement of Critical Shoulder Angle (CSA), Lateral Acromion Angle (LAA), and Acromion Index (AI) from Shoulder X-ray Images." Diagnostics 14, no. 18 (2024): 2092. http://dx.doi.org/10.3390/diagnostics14182092.

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Background: The accurate and effective evaluation of parameters such as critical shoulder angle, lateral acromion angle, and acromion index from shoulder X-ray images is crucial for identifying pathological changes and assessing disease risk in the shoulder joint. Methods: In this study, a YOLOv8-based model was developed to automatically measure these three parameters together, contributing to the existing literature. Initially, YOLOv8 was used to segment the acromion, glenoid, and humerus regions, after which the CSA, LAA angles, and AI between these regions were calculated. The MURA dataset

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