Anatomical structure characterization of fetal ultrasound images using texture‐based segmentation technique via an interactive MATLAB application
Objective To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software. Methods Prospective descriptive observational study with an analy...
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Veröffentlicht in: | Journal of clinical ultrasound 2024-02, Vol.52 (2), p.189-200 |
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creator | Molina‐Giraldo, Saulo Torres‐Valencia, Natalia Torres‐Valencia, Cristian Restrepo, Hector Fabio |
description | Objective
To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software.
Methods
Prospective descriptive observational study with an analytical component. 2D fetal ultrasound images were acquired in patients admitted to the Maternal Fetal Medicine Unit of the Hospital de San José, Bogotá‐Colombia. These images were loaded into the developed application to carry out the segmentation and characterization stages by means of 23 numerical texture descriptors. The data were analyzed with central tendency measures and through an embedding process and Euclidean distance.
Results
Forty ultrasound images were included, characterizing 54 structures of the fetal placenta, skull, thorax, and abdomen. By embedding the descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.
Conclusion
The texture characterization of the labeled structures in fetal ultrasound images through the numerical descriptors allows the accurate discrimination of these structures.
A characterization stage with 23 numerical texture descriptors was performed over 40 fetal ultrasound images, after applying an image segmentation technique through an application developed in MATLAB. By embedding these descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance. |
doi_str_mv | 10.1002/jcu.23604 |
format | Article |
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To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software.
Methods
Prospective descriptive observational study with an analytical component. 2D fetal ultrasound images were acquired in patients admitted to the Maternal Fetal Medicine Unit of the Hospital de San José, Bogotá‐Colombia. These images were loaded into the developed application to carry out the segmentation and characterization stages by means of 23 numerical texture descriptors. The data were analyzed with central tendency measures and through an embedding process and Euclidean distance.
Results
Forty ultrasound images were included, characterizing 54 structures of the fetal placenta, skull, thorax, and abdomen. By embedding the descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.
Conclusion
The texture characterization of the labeled structures in fetal ultrasound images through the numerical descriptors allows the accurate discrimination of these structures.
A characterization stage with 23 numerical texture descriptors was performed over 40 fetal ultrasound images, after applying an image segmentation technique through an application developed in MATLAB. By embedding these descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.</description><identifier>ISSN: 0091-2751</identifier><identifier>EISSN: 1097-0096</identifier><identifier>DOI: 10.1002/jcu.23604</identifier><identifier>PMID: 37994115</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>diagnostic imaging ; Differentiation ; Embedding ; Euclidean geometry ; Female ; Fetus - diagnostic imaging ; Fetuses ; Humans ; Image acquisition ; Image processing ; Image Processing, Computer-Assisted - methods ; Image segmentation ; MATLAB ; Observational studies ; Placenta ; Pregnancy ; prenatal diagnosis ; prenatal ultrasonography ; Prospective Studies ; Structural analysis ; Texture ; Thorax ; Two dimensional analysis ; Ultrasonic imaging ; Ultrasonography ; Ultrasonography, Prenatal - methods ; Ultrasound</subject><ispartof>Journal of clinical ultrasound, 2024-02, Vol.52 (2), p.189-200</ispartof><rights>2023 Wiley Periodicals LLC.</rights><rights>2024 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3134-4aafa40bf0d9de237d65d2c90a8c8ca49a0002b7c3ffd52a625a7ce4bef9a9ac3</cites><orcidid>0000-0001-6019-938X ; 0000-0001-9345-2847</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjcu.23604$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjcu.23604$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37994115$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Molina‐Giraldo, Saulo</creatorcontrib><creatorcontrib>Torres‐Valencia, Natalia</creatorcontrib><creatorcontrib>Torres‐Valencia, Cristian</creatorcontrib><creatorcontrib>Restrepo, Hector Fabio</creatorcontrib><title>Anatomical structure characterization of fetal ultrasound images using texture‐based segmentation technique via an interactive MATLAB application</title><title>Journal of clinical ultrasound</title><addtitle>J Clin Ultrasound</addtitle><description>Objective
To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software.
Methods
Prospective descriptive observational study with an analytical component. 2D fetal ultrasound images were acquired in patients admitted to the Maternal Fetal Medicine Unit of the Hospital de San José, Bogotá‐Colombia. These images were loaded into the developed application to carry out the segmentation and characterization stages by means of 23 numerical texture descriptors. The data were analyzed with central tendency measures and through an embedding process and Euclidean distance.
Results
Forty ultrasound images were included, characterizing 54 structures of the fetal placenta, skull, thorax, and abdomen. By embedding the descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.
Conclusion
The texture characterization of the labeled structures in fetal ultrasound images through the numerical descriptors allows the accurate discrimination of these structures.
A characterization stage with 23 numerical texture descriptors was performed over 40 fetal ultrasound images, after applying an image segmentation technique through an application developed in MATLAB. By embedding these descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.</description><subject>diagnostic imaging</subject><subject>Differentiation</subject><subject>Embedding</subject><subject>Euclidean geometry</subject><subject>Female</subject><subject>Fetus - diagnostic imaging</subject><subject>Fetuses</subject><subject>Humans</subject><subject>Image acquisition</subject><subject>Image processing</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Image segmentation</subject><subject>MATLAB</subject><subject>Observational studies</subject><subject>Placenta</subject><subject>Pregnancy</subject><subject>prenatal diagnosis</subject><subject>prenatal ultrasonography</subject><subject>Prospective Studies</subject><subject>Structural analysis</subject><subject>Texture</subject><subject>Thorax</subject><subject>Two dimensional analysis</subject><subject>Ultrasonic imaging</subject><subject>Ultrasonography</subject><subject>Ultrasonography, Prenatal - methods</subject><subject>Ultrasound</subject><issn>0091-2751</issn><issn>1097-0096</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kc1u1DAURi0EokNhwQsgS2xgkdZ2nGS8nI4KLRrEpl1bN87N1KPEGfxTWlY8AhJvyJPgIYUFEqu7Off48_0IecnZCWdMnO5MOhFlzeQjsuBMNQVjqn5MFnnwQjQVPyLPQtgxxuqqqp6So7JRSnJeLciPlYM4jdbAQEP0ycTkkZob8GAievsVop0cnXraY8xMGqKHMCXXUTvCFgNNwbotjXh32Pz57XsLATsacDuii_N2RHPj7OeE9NYCBUety-78gL1F-nF1tVmdUdjvh5ziwD8nT3oYAr54mMfk-t351fqi2Hx6f7lebQpT8lIWEqAHydqedapDUTZdXXXCKAZLszQgFeQPi7YxZd93lYBaVNAYlC32ChSY8pi8mb17P-VwIerRBoPDAA6nFLRYKqGkypfN6Ot_0N2UvMvptFCikkIyXmbq7UwZP4Xgsdd7n6_k7zVn-tCUzk3p301l9tWDMbUjdn_JP9Vk4HQGvtgB7_9v0h_W17PyF3rwoko</recordid><startdate>202402</startdate><enddate>202402</enddate><creator>Molina‐Giraldo, Saulo</creator><creator>Torres‐Valencia, Natalia</creator><creator>Torres‐Valencia, Cristian</creator><creator>Restrepo, Hector Fabio</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6019-938X</orcidid><orcidid>https://orcid.org/0000-0001-9345-2847</orcidid></search><sort><creationdate>202402</creationdate><title>Anatomical structure characterization of fetal ultrasound images using texture‐based segmentation technique via an interactive MATLAB application</title><author>Molina‐Giraldo, Saulo ; Torres‐Valencia, Natalia ; Torres‐Valencia, Cristian ; Restrepo, Hector Fabio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3134-4aafa40bf0d9de237d65d2c90a8c8ca49a0002b7c3ffd52a625a7ce4bef9a9ac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>diagnostic imaging</topic><topic>Differentiation</topic><topic>Embedding</topic><topic>Euclidean geometry</topic><topic>Female</topic><topic>Fetus - diagnostic imaging</topic><topic>Fetuses</topic><topic>Humans</topic><topic>Image acquisition</topic><topic>Image processing</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Image segmentation</topic><topic>MATLAB</topic><topic>Observational studies</topic><topic>Placenta</topic><topic>Pregnancy</topic><topic>prenatal diagnosis</topic><topic>prenatal ultrasonography</topic><topic>Prospective Studies</topic><topic>Structural analysis</topic><topic>Texture</topic><topic>Thorax</topic><topic>Two dimensional analysis</topic><topic>Ultrasonic imaging</topic><topic>Ultrasonography</topic><topic>Ultrasonography, Prenatal - methods</topic><topic>Ultrasound</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Molina‐Giraldo, Saulo</creatorcontrib><creatorcontrib>Torres‐Valencia, Natalia</creatorcontrib><creatorcontrib>Torres‐Valencia, Cristian</creatorcontrib><creatorcontrib>Restrepo, Hector Fabio</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of clinical ultrasound</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Molina‐Giraldo, Saulo</au><au>Torres‐Valencia, Natalia</au><au>Torres‐Valencia, Cristian</au><au>Restrepo, Hector Fabio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Anatomical structure characterization of fetal ultrasound images using texture‐based segmentation technique via an interactive MATLAB application</atitle><jtitle>Journal of clinical ultrasound</jtitle><addtitle>J Clin Ultrasound</addtitle><date>2024-02</date><risdate>2024</risdate><volume>52</volume><issue>2</issue><spage>189</spage><epage>200</epage><pages>189-200</pages><issn>0091-2751</issn><eissn>1097-0096</eissn><abstract>Objective
To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software.
Methods
Prospective descriptive observational study with an analytical component. 2D fetal ultrasound images were acquired in patients admitted to the Maternal Fetal Medicine Unit of the Hospital de San José, Bogotá‐Colombia. These images were loaded into the developed application to carry out the segmentation and characterization stages by means of 23 numerical texture descriptors. The data were analyzed with central tendency measures and through an embedding process and Euclidean distance.
Results
Forty ultrasound images were included, characterizing 54 structures of the fetal placenta, skull, thorax, and abdomen. By embedding the descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.
Conclusion
The texture characterization of the labeled structures in fetal ultrasound images through the numerical descriptors allows the accurate discrimination of these structures.
A characterization stage with 23 numerical texture descriptors was performed over 40 fetal ultrasound images, after applying an image segmentation technique through an application developed in MATLAB. By embedding these descriptors, the differentiation of biologically known structures as distinct was achieved, as well as the non‐differentiation of similar structures, evidenced using 2D and 3D graphs and numerical data with statistical significance.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>37994115</pmid><doi>10.1002/jcu.23604</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-6019-938X</orcidid><orcidid>https://orcid.org/0000-0001-9345-2847</orcidid></addata></record> |
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subjects | diagnostic imaging Differentiation Embedding Euclidean geometry Female Fetus - diagnostic imaging Fetuses Humans Image acquisition Image processing Image Processing, Computer-Assisted - methods Image segmentation MATLAB Observational studies Placenta Pregnancy prenatal diagnosis prenatal ultrasonography Prospective Studies Structural analysis Texture Thorax Two dimensional analysis Ultrasonic imaging Ultrasonography Ultrasonography, Prenatal - methods Ultrasound |
title | Anatomical structure characterization of fetal ultrasound images using texture‐based segmentation technique via an interactive MATLAB application |
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