METHOD OF SEGMENTING NEGATIVE VOLUMES IN COMPLEX 3D STRUCTURES
The present disclosure is related to the field of 3D image segmentation, in particular to a method of automatically determining the contours of the constituent parts of complex (compound) structures on 3D images using technique of segmenting negative volumes and deep neural network. The technical re...
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| creator | DYLOV, Dmitry Vladimirovich MASLOV, Maksim Vyacheslavovich ROGOV, Oleg Yurevich BELIKOVA, Kristina Nikolaevna RYBAKOV, Aleksandr Vladimirovich |
| description | The present disclosure is related to the field of 3D image segmentation, in particular to a method of automatically determining the contours of the constituent parts of complex (compound) structures on 3D images using technique of segmenting negative volumes and deep neural network. The technical result of the claimed invention consists in providing faster and more accurate negative volume segmentation of the compound 3D structures of living and non-living objects. The claimed result is achieved due to implementation of the method, including the following steps: obtaining 3D image data of the compound 3D structure; selecting a volume of interest, comprising a negative volume on the obtained 3D image data of the compound 3D structure, wherein the negative volume is an inner space between at least two adjacent components of the compound 3D structure; segmenting the adjacent components of the compound 3D structure; 3D reconstructing the segmented adjacent components; segmenting the negative volume, wherein segmentation of the negative volume including at least the following: mesh inflating an inner surface of the first reconstructed component to fit into an inner surface of the second reconstructed component until the entire negative volume is occupied, and obtaining the inflated first reconstructed component, wherein surface mesh inflation including at least the following: obtaining vertices of the first and the second reconstructed components; obtaining number of vertices of the first and the second reconstructed components; obtaining faces of the first and the second reconstructed components based on obtained vertices and number of vertices; obtaining normal vector to each face of the first reconstructed component; obtaining coordinates of each vertex of the first reconstructed component; while the first reconstructed component does not intersect with the second reconstructed component extruding each face of the first reconstructed component separately along local normal and shifting coordinates of each vertex of the first reconstructed component increasing parameters, comprising length, radius, depth; subtracting the first reconstructed component from the inflated first reconstructed component; 3D reconstructing the inner space between the adjacent components of the compound 3D structure.
La présente divulgation, qui relève du domaine de la segmentation d'images 3D, concerne en particulier un procédé de détermination automatique des contours des parties c |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_WO2024136692A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>WO2024136692A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_WO2024136692A13</originalsourceid><addsrcrecordid>eNrjZLDzdQ3x8HdR8HdTCHZ193X1C_H0c1fwc3V3DPEMc1UI8_cJ9XUNVvD0U3D29w3wcY1QMHZRCA4JCnUOCQ1yDeZhYE1LzClO5YXS3AzKbq4hzh66qQX58anFBYnJqXmpJfHh_kYGRiaGxmZmlkaOhsbEqQIAChIrKg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>METHOD OF SEGMENTING NEGATIVE VOLUMES IN COMPLEX 3D STRUCTURES</title><source>esp@cenet</source><creator>DYLOV, Dmitry Vladimirovich ; MASLOV, Maksim Vyacheslavovich ; ROGOV, Oleg Yurevich ; BELIKOVA, Kristina Nikolaevna ; RYBAKOV, Aleksandr Vladimirovich</creator><creatorcontrib>DYLOV, Dmitry Vladimirovich ; MASLOV, Maksim Vyacheslavovich ; ROGOV, Oleg Yurevich ; BELIKOVA, Kristina Nikolaevna ; RYBAKOV, Aleksandr Vladimirovich</creatorcontrib><description>The present disclosure is related to the field of 3D image segmentation, in particular to a method of automatically determining the contours of the constituent parts of complex (compound) structures on 3D images using technique of segmenting negative volumes and deep neural network. The technical result of the claimed invention consists in providing faster and more accurate negative volume segmentation of the compound 3D structures of living and non-living objects. The claimed result is achieved due to implementation of the method, including the following steps: obtaining 3D image data of the compound 3D structure; selecting a volume of interest, comprising a negative volume on the obtained 3D image data of the compound 3D structure, wherein the negative volume is an inner space between at least two adjacent components of the compound 3D structure; segmenting the adjacent components of the compound 3D structure; 3D reconstructing the segmented adjacent components; segmenting the negative volume, wherein segmentation of the negative volume including at least the following: mesh inflating an inner surface of the first reconstructed component to fit into an inner surface of the second reconstructed component until the entire negative volume is occupied, and obtaining the inflated first reconstructed component, wherein surface mesh inflation including at least the following: obtaining vertices of the first and the second reconstructed components; obtaining number of vertices of the first and the second reconstructed components; obtaining faces of the first and the second reconstructed components based on obtained vertices and number of vertices; obtaining normal vector to each face of the first reconstructed component; obtaining coordinates of each vertex of the first reconstructed component; while the first reconstructed component does not intersect with the second reconstructed component extruding each face of the first reconstructed component separately along local normal and shifting coordinates of each vertex of the first reconstructed component increasing parameters, comprising length, radius, depth; subtracting the first reconstructed component from the inflated first reconstructed component; 3D reconstructing the inner space between the adjacent components of the compound 3D structure.
La présente divulgation, qui relève du domaine de la segmentation d'images 3D, concerne en particulier un procédé de détermination automatique des contours des parties constitutives de structures complexes (composées) sur des images 3D à l'aide d'une technique de segmentation de volumes négatifs et d'un réseau neuronal profond. Le résultat technique de la présente invention consiste en une segmentation de volumes négatifs plus rapide et plus précise des structures 3D composées d'objets vivants et non vivants. Le résultat revendiqué est obtenu en raison de la mise en œuvre du procédé, incluant les étapes suivantes : l'obtention de données d'image 3D de la structure 3D composée; la sélection d'un volume d'intérêt, comprenant un volume négatif sur les données d'image 3D obtenues de la structure 3D composite, le volume négatif étant un espace interne entre au moins deux composants adjacents de la structure 3D composite; la segmentation des composants adjacents de la structure 3D composite; la reconstruction 3D des composants adjacents segmentés; la segmentation du volume négatif, la segmentation du volume négatif incluant au moins ce qui suit : le gonflement du maillage d'une surface interne du premier composant reconstruit pour l'ajuster dans une surface interne du second composant reconstruit jusqu'à ce que tout le volume négatif soit occupé, et l'obtention du premier composant reconstruit gonflé, le gonflement du maillage de la surface incluant au moins ce qui suit : l'obtention de sommets des premier et second composants reconstruits; l'obtention d'un certain nombre de sommets des premier et second composants reconstruits; l'obtention des faces des premier et second composants reconstruits sur la base des sommets et du nombre de sommets obtenus; l'obtention des coordonnées de chaque sommet du premier composant reconstruit; tandis que le premier composant reconstruit ne coupe pas le second composant reconstruit, l'extrusion de chaque face du premier composant reconstruit séparément de la normale locale et le décalage de coordonnées de chaque sommet du premier composant reconstruit par augmentation de paramètres, comprenant la longueur, le rayon, la profondeur; le retrait soustraction du premier composant reconstruit du premier composant reconstruit gonflé; la reconstruction 3D de l'espace interne entre les composants adjacents de la structure 3D composite.</description><language>eng ; fre</language><subject>CALCULATING ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240627&DB=EPODOC&CC=WO&NR=2024136692A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76418</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240627&DB=EPODOC&CC=WO&NR=2024136692A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>DYLOV, Dmitry Vladimirovich</creatorcontrib><creatorcontrib>MASLOV, Maksim Vyacheslavovich</creatorcontrib><creatorcontrib>ROGOV, Oleg Yurevich</creatorcontrib><creatorcontrib>BELIKOVA, Kristina Nikolaevna</creatorcontrib><creatorcontrib>RYBAKOV, Aleksandr Vladimirovich</creatorcontrib><title>METHOD OF SEGMENTING NEGATIVE VOLUMES IN COMPLEX 3D STRUCTURES</title><description>The present disclosure is related to the field of 3D image segmentation, in particular to a method of automatically determining the contours of the constituent parts of complex (compound) structures on 3D images using technique of segmenting negative volumes and deep neural network. The technical result of the claimed invention consists in providing faster and more accurate negative volume segmentation of the compound 3D structures of living and non-living objects. The claimed result is achieved due to implementation of the method, including the following steps: obtaining 3D image data of the compound 3D structure; selecting a volume of interest, comprising a negative volume on the obtained 3D image data of the compound 3D structure, wherein the negative volume is an inner space between at least two adjacent components of the compound 3D structure; segmenting the adjacent components of the compound 3D structure; 3D reconstructing the segmented adjacent components; segmenting the negative volume, wherein segmentation of the negative volume including at least the following: mesh inflating an inner surface of the first reconstructed component to fit into an inner surface of the second reconstructed component until the entire negative volume is occupied, and obtaining the inflated first reconstructed component, wherein surface mesh inflation including at least the following: obtaining vertices of the first and the second reconstructed components; obtaining number of vertices of the first and the second reconstructed components; obtaining faces of the first and the second reconstructed components based on obtained vertices and number of vertices; obtaining normal vector to each face of the first reconstructed component; obtaining coordinates of each vertex of the first reconstructed component; while the first reconstructed component does not intersect with the second reconstructed component extruding each face of the first reconstructed component separately along local normal and shifting coordinates of each vertex of the first reconstructed component increasing parameters, comprising length, radius, depth; subtracting the first reconstructed component from the inflated first reconstructed component; 3D reconstructing the inner space between the adjacent components of the compound 3D structure.
La présente divulgation, qui relève du domaine de la segmentation d'images 3D, concerne en particulier un procédé de détermination automatique des contours des parties constitutives de structures complexes (composées) sur des images 3D à l'aide d'une technique de segmentation de volumes négatifs et d'un réseau neuronal profond. Le résultat technique de la présente invention consiste en une segmentation de volumes négatifs plus rapide et plus précise des structures 3D composées d'objets vivants et non vivants. Le résultat revendiqué est obtenu en raison de la mise en œuvre du procédé, incluant les étapes suivantes : l'obtention de données d'image 3D de la structure 3D composée; la sélection d'un volume d'intérêt, comprenant un volume négatif sur les données d'image 3D obtenues de la structure 3D composite, le volume négatif étant un espace interne entre au moins deux composants adjacents de la structure 3D composite; la segmentation des composants adjacents de la structure 3D composite; la reconstruction 3D des composants adjacents segmentés; la segmentation du volume négatif, la segmentation du volume négatif incluant au moins ce qui suit : le gonflement du maillage d'une surface interne du premier composant reconstruit pour l'ajuster dans une surface interne du second composant reconstruit jusqu'à ce que tout le volume négatif soit occupé, et l'obtention du premier composant reconstruit gonflé, le gonflement du maillage de la surface incluant au moins ce qui suit : l'obtention de sommets des premier et second composants reconstruits; l'obtention d'un certain nombre de sommets des premier et second composants reconstruits; l'obtention des faces des premier et second composants reconstruits sur la base des sommets et du nombre de sommets obtenus; l'obtention des coordonnées de chaque sommet du premier composant reconstruit; tandis que le premier composant reconstruit ne coupe pas le second composant reconstruit, l'extrusion de chaque face du premier composant reconstruit séparément de la normale locale et le décalage de coordonnées de chaque sommet du premier composant reconstruit par augmentation de paramètres, comprenant la longueur, le rayon, la profondeur; le retrait soustraction du premier composant reconstruit du premier composant reconstruit gonflé; la reconstruction 3D de l'espace interne entre les composants adjacents de la structure 3D composite.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLDzdQ3x8HdR8HdTCHZ193X1C_H0c1fwc3V3DPEMc1UI8_cJ9XUNVvD0U3D29w3wcY1QMHZRCA4JCnUOCQ1yDeZhYE1LzClO5YXS3AzKbq4hzh66qQX58anFBYnJqXmpJfHh_kYGRiaGxmZmlkaOhsbEqQIAChIrKg</recordid><startdate>20240627</startdate><enddate>20240627</enddate><creator>DYLOV, Dmitry Vladimirovich</creator><creator>MASLOV, Maksim Vyacheslavovich</creator><creator>ROGOV, Oleg Yurevich</creator><creator>BELIKOVA, Kristina Nikolaevna</creator><creator>RYBAKOV, Aleksandr Vladimirovich</creator><scope>EVB</scope></search><sort><creationdate>20240627</creationdate><title>METHOD OF SEGMENTING NEGATIVE VOLUMES IN COMPLEX 3D STRUCTURES</title><author>DYLOV, Dmitry Vladimirovich ; MASLOV, Maksim Vyacheslavovich ; ROGOV, Oleg Yurevich ; BELIKOVA, Kristina Nikolaevna ; RYBAKOV, Aleksandr Vladimirovich</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_WO2024136692A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>DYLOV, Dmitry Vladimirovich</creatorcontrib><creatorcontrib>MASLOV, Maksim Vyacheslavovich</creatorcontrib><creatorcontrib>ROGOV, Oleg Yurevich</creatorcontrib><creatorcontrib>BELIKOVA, Kristina Nikolaevna</creatorcontrib><creatorcontrib>RYBAKOV, Aleksandr Vladimirovich</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>DYLOV, Dmitry Vladimirovich</au><au>MASLOV, Maksim Vyacheslavovich</au><au>ROGOV, Oleg Yurevich</au><au>BELIKOVA, Kristina Nikolaevna</au><au>RYBAKOV, Aleksandr Vladimirovich</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>METHOD OF SEGMENTING NEGATIVE VOLUMES IN COMPLEX 3D STRUCTURES</title><date>2024-06-27</date><risdate>2024</risdate><abstract>The present disclosure is related to the field of 3D image segmentation, in particular to a method of automatically determining the contours of the constituent parts of complex (compound) structures on 3D images using technique of segmenting negative volumes and deep neural network. The technical result of the claimed invention consists in providing faster and more accurate negative volume segmentation of the compound 3D structures of living and non-living objects. The claimed result is achieved due to implementation of the method, including the following steps: obtaining 3D image data of the compound 3D structure; selecting a volume of interest, comprising a negative volume on the obtained 3D image data of the compound 3D structure, wherein the negative volume is an inner space between at least two adjacent components of the compound 3D structure; segmenting the adjacent components of the compound 3D structure; 3D reconstructing the segmented adjacent components; segmenting the negative volume, wherein segmentation of the negative volume including at least the following: mesh inflating an inner surface of the first reconstructed component to fit into an inner surface of the second reconstructed component until the entire negative volume is occupied, and obtaining the inflated first reconstructed component, wherein surface mesh inflation including at least the following: obtaining vertices of the first and the second reconstructed components; obtaining number of vertices of the first and the second reconstructed components; obtaining faces of the first and the second reconstructed components based on obtained vertices and number of vertices; obtaining normal vector to each face of the first reconstructed component; obtaining coordinates of each vertex of the first reconstructed component; while the first reconstructed component does not intersect with the second reconstructed component extruding each face of the first reconstructed component separately along local normal and shifting coordinates of each vertex of the first reconstructed component increasing parameters, comprising length, radius, depth; subtracting the first reconstructed component from the inflated first reconstructed component; 3D reconstructing the inner space between the adjacent components of the compound 3D structure.
La présente divulgation, qui relève du domaine de la segmentation d'images 3D, concerne en particulier un procédé de détermination automatique des contours des parties constitutives de structures complexes (composées) sur des images 3D à l'aide d'une technique de segmentation de volumes négatifs et d'un réseau neuronal profond. Le résultat technique de la présente invention consiste en une segmentation de volumes négatifs plus rapide et plus précise des structures 3D composées d'objets vivants et non vivants. Le résultat revendiqué est obtenu en raison de la mise en œuvre du procédé, incluant les étapes suivantes : l'obtention de données d'image 3D de la structure 3D composée; la sélection d'un volume d'intérêt, comprenant un volume négatif sur les données d'image 3D obtenues de la structure 3D composite, le volume négatif étant un espace interne entre au moins deux composants adjacents de la structure 3D composite; la segmentation des composants adjacents de la structure 3D composite; la reconstruction 3D des composants adjacents segmentés; la segmentation du volume négatif, la segmentation du volume négatif incluant au moins ce qui suit : le gonflement du maillage d'une surface interne du premier composant reconstruit pour l'ajuster dans une surface interne du second composant reconstruit jusqu'à ce que tout le volume négatif soit occupé, et l'obtention du premier composant reconstruit gonflé, le gonflement du maillage de la surface incluant au moins ce qui suit : l'obtention de sommets des premier et second composants reconstruits; l'obtention d'un certain nombre de sommets des premier et second composants reconstruits; l'obtention des faces des premier et second composants reconstruits sur la base des sommets et du nombre de sommets obtenus; l'obtention des coordonnées de chaque sommet du premier composant reconstruit; tandis que le premier composant reconstruit ne coupe pas le second composant reconstruit, l'extrusion de chaque face du premier composant reconstruit séparément de la normale locale et le décalage de coordonnées de chaque sommet du premier composant reconstruit par augmentation de paramètres, comprenant la longueur, le rayon, la profondeur; le retrait soustraction du premier composant reconstruit du premier composant reconstruit gonflé; la reconstruction 3D de l'espace interne entre les composants adjacents de la structure 3D composite.</abstract><oa>free_for_read</oa></addata></record> |
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| title | METHOD OF SEGMENTING NEGATIVE VOLUMES IN COMPLEX 3D STRUCTURES |
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