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Images illustrating <t>the</t> <t>Imaris</t> <t>workflow</t> developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x
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Images illustrating <t>the</t> <t>Imaris</t> <t>workflow</t> developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x
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Images illustrating <t>the</t> <t>Imaris</t> <t>workflow</t> developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x
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Images illustrating <t>the</t> <t>Imaris</t> <t>workflow</t> developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x
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Images illustrating <t>the</t> <t>Imaris</t> <t>workflow</t> developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x
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Images illustrating <t>the</t> <t>Imaris</t> <t>workflow</t> developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x
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Image Search Results


Images illustrating the Imaris workflow developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x

Journal: Cerebellum (London, England)

Article Title: Innovative 3D-Image Analysis of Cerebellar Vascularization Highlights Angiogenic Gene Dysregulations in a Murine Model of Apnea of Prematurity

doi: 10.1007/s12311-026-02006-1

Figure Lengend Snippet: Images illustrating the Imaris workflow developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x

Article Snippet: IH: intermittent hypoxia; N: normoxia; Px: postnatal day x Fig. 2 Images illustrating the Imaris workflow developed for the vascular network modeling.

Techniques: Software

Images illustrating the Imaris workflow developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x

Journal: Cerebellum (London, England)

Article Title: Innovative 3D-Image Analysis of Cerebellar Vascularization Highlights Angiogenic Gene Dysregulations in a Murine Model of Apnea of Prematurity

doi: 10.1007/s12311-026-02006-1

Figure Lengend Snippet: Images illustrating the Imaris workflow developed for the vascular network modeling. A–I: Sequential workflow steps allowing the analysis of the cerebellar vascular network of a P4 mouse cerebellum on the Imaris software. From a 3D lightsheet acquisition (A) , the cerebellum is delineated (B) and a mask is created (C) . Within that selected volume, the cerebellar vascularization is segmented (D) , which allows the network visualization (E) and the separation of a deep and a superficial network (F) . Then the threshold of seedpoints is defined (G) , and thanks to the artificial intelligence module (AI), Imaris is able to discriminate “true” (blue) and “false” (red) seedpoints (H) , and “true” (blue) and “false” (red) segments (I) . AI: artificial intelligence; Px: postnatal day x

Article Snippet: Moreover, to correlate putative modifications of gene expression with defects in vessel morphology, we developed an image analysis workflow using both Imaris and VesselVio software to visualize the cerebellar vascularization in 3D during postnatal development and obtain comparable quantitative parameters between normoxic and IH conditions.

Techniques: Software