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3.0 t dataset  (Philips Healthcare)

 
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    Structured Review

    Philips Healthcare 3.0 t dataset
    In (A) and (B), the DMNs obtained with different initial seed regions of interest (ROIs) using sCCA (A) and siCCA (B) are displayed in two axial slices ( z = +30 and −27 for the Philips 3.0 T dataset; z = +30 and −21 for the Siemens 1.5 T dataset). The siCCA-derived DMNs are shown in additional axial slices in (C). White arrows and asterisks indicate the regions with different peak locations (PHG, temporal poles and thalamus) and distinct regions (a ACC/caudate/thalamus cluster for Philips 3.0 T and bilateral middle OFC for Siemens 1.5 T) in the two datasets respectively. The VBS net index depicting the similarity among the DMNs obtained with different initial seed regions of interest was plotted in (D). The abscissa label in (D) describes the initial seed ROIs being compared. The similarity between the siCCA-derived DMN and the sCCA-derived DMNs with different initial seed ROIs was evaluated in (E). Please refer to the Selection of Initial seed ROIs section for definitions of the abbreviations for the seed ROIs.
    3.0 T Dataset, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/3.0 t dataset/product/Philips Healthcare
    Average 90 stars, based on 1 article reviews
    3.0 t dataset - by Bioz Stars, 2026-05
    90/100 stars

    Images

    1) Product Images from "Iterative Cross-Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data"

    Article Title: Iterative Cross-Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0058653

    In (A) and (B), the DMNs obtained with different initial seed regions of interest (ROIs) using sCCA (A) and siCCA (B) are displayed in two axial slices ( z = +30 and −27 for the Philips 3.0 T dataset; z = +30 and −21 for the Siemens 1.5 T dataset). The siCCA-derived DMNs are shown in additional axial slices in (C). White arrows and asterisks indicate the regions with different peak locations (PHG, temporal poles and thalamus) and distinct regions (a ACC/caudate/thalamus cluster for Philips 3.0 T and bilateral middle OFC for Siemens 1.5 T) in the two datasets respectively. The VBS net index depicting the similarity among the DMNs obtained with different initial seed regions of interest was plotted in (D). The abscissa label in (D) describes the initial seed ROIs being compared. The similarity between the siCCA-derived DMN and the sCCA-derived DMNs with different initial seed ROIs was evaluated in (E). Please refer to the Selection of Initial seed ROIs section for definitions of the abbreviations for the seed ROIs.
    Figure Legend Snippet: In (A) and (B), the DMNs obtained with different initial seed regions of interest (ROIs) using sCCA (A) and siCCA (B) are displayed in two axial slices ( z = +30 and −27 for the Philips 3.0 T dataset; z = +30 and −21 for the Siemens 1.5 T dataset). The siCCA-derived DMNs are shown in additional axial slices in (C). White arrows and asterisks indicate the regions with different peak locations (PHG, temporal poles and thalamus) and distinct regions (a ACC/caudate/thalamus cluster for Philips 3.0 T and bilateral middle OFC for Siemens 1.5 T) in the two datasets respectively. The VBS net index depicting the similarity among the DMNs obtained with different initial seed regions of interest was plotted in (D). The abscissa label in (D) describes the initial seed ROIs being compared. The similarity between the siCCA-derived DMN and the sCCA-derived DMNs with different initial seed ROIs was evaluated in (E). Please refer to the Selection of Initial seed ROIs section for definitions of the abbreviations for the seed ROIs.

    Techniques Used: Derivative Assay, Selection



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    3.0 t dataset  (Philips Healthcare)
    90
    Philips Healthcare 3.0 t dataset
    In (A) and (B), the DMNs obtained with different initial seed regions of interest (ROIs) using sCCA (A) and siCCA (B) are displayed in two axial slices ( z = +30 and −27 for the Philips 3.0 T dataset; z = +30 and −21 for the Siemens 1.5 T dataset). The siCCA-derived DMNs are shown in additional axial slices in (C). White arrows and asterisks indicate the regions with different peak locations (PHG, temporal poles and thalamus) and distinct regions (a ACC/caudate/thalamus cluster for Philips 3.0 T and bilateral middle OFC for Siemens 1.5 T) in the two datasets respectively. The VBS net index depicting the similarity among the DMNs obtained with different initial seed regions of interest was plotted in (D). The abscissa label in (D) describes the initial seed ROIs being compared. The similarity between the siCCA-derived DMN and the sCCA-derived DMNs with different initial seed ROIs was evaluated in (E). Please refer to the Selection of Initial seed ROIs section for definitions of the abbreviations for the seed ROIs.
    3.0 T Dataset, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/3.0 t dataset/product/Philips Healthcare
    Average 90 stars, based on 1 article reviews
    3.0 t dataset - by Bioz Stars, 2026-05
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    In (A) and (B), the DMNs obtained with different initial seed regions of interest (ROIs) using sCCA (A) and siCCA (B) are displayed in two axial slices ( z = +30 and −27 for the Philips 3.0 T dataset; z = +30 and −21 for the Siemens 1.5 T dataset). The siCCA-derived DMNs are shown in additional axial slices in (C). White arrows and asterisks indicate the regions with different peak locations (PHG, temporal poles and thalamus) and distinct regions (a ACC/caudate/thalamus cluster for Philips 3.0 T and bilateral middle OFC for Siemens 1.5 T) in the two datasets respectively. The VBS net index depicting the similarity among the DMNs obtained with different initial seed regions of interest was plotted in (D). The abscissa label in (D) describes the initial seed ROIs being compared. The similarity between the siCCA-derived DMN and the sCCA-derived DMNs with different initial seed ROIs was evaluated in (E). Please refer to the Selection of Initial seed ROIs section for definitions of the abbreviations for the seed ROIs.

    Journal: PLoS ONE

    Article Title: Iterative Cross-Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data

    doi: 10.1371/journal.pone.0058653

    Figure Lengend Snippet: In (A) and (B), the DMNs obtained with different initial seed regions of interest (ROIs) using sCCA (A) and siCCA (B) are displayed in two axial slices ( z = +30 and −27 for the Philips 3.0 T dataset; z = +30 and −21 for the Siemens 1.5 T dataset). The siCCA-derived DMNs are shown in additional axial slices in (C). White arrows and asterisks indicate the regions with different peak locations (PHG, temporal poles and thalamus) and distinct regions (a ACC/caudate/thalamus cluster for Philips 3.0 T and bilateral middle OFC for Siemens 1.5 T) in the two datasets respectively. The VBS net index depicting the similarity among the DMNs obtained with different initial seed regions of interest was plotted in (D). The abscissa label in (D) describes the initial seed ROIs being compared. The similarity between the siCCA-derived DMN and the sCCA-derived DMNs with different initial seed ROIs was evaluated in (E). Please refer to the Selection of Initial seed ROIs section for definitions of the abbreviations for the seed ROIs.

    Article Snippet: The remaining volumes (i.e., 210 for Philips 3.0 T dataset and 170 for Siemens 1.5 T dataset) were put into subsequent processing procedures, including slice timing and head motion corrections, spatial normalization to the standard Montreal Neurological Institute (MNI) space (i.e., all data resampled to a voxel size of 3 mm×3 mm×3 mm), spatial smoothing with a 6-mm full width at half maximum (FWHM) isotropic Gaussian kernel, removal of linear drift and temporal band-pass filtering (0.01–0.08 Hz).

    Techniques: Derivative Assay, Selection