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Abacus Concepts 3dcnn
3dcnn, supplied by Abacus Concepts, 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/3dcnn/product/Abacus Concepts
Average 90 stars, based on 1 article reviews
3dcnn - by Bioz Stars, 2026-05
90/100 stars

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Image Search Results


Results of spatial connected component analysis for the neurodegenerative brain regions in AD sMRI images

Journal: Advanced Science

Article Title: Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease

doi: 10.1002/advs.202204717

Figure Lengend Snippet: Results of spatial connected component analysis for the neurodegenerative brain regions in AD sMRI images

Article Snippet: Plus, in the Supporting Information, the scatter diagram of P ‐score whole and AD (softmax) predictive score obtained by Ensemble 3DCNN for 638 AD sMRI images as shown in Table and Figure 2 was plotted to exhibit the association between P‐score at whole‐brain level and AD probability output from Ensemble 3DCNN , that is, AD (softmax) predictive scores, to some degree.

Techniques:

Results of spatial‐temporal connected component analysis for the neurodegenerative brain regions in longitudinal AD sMRI images

Journal: Advanced Science

Article Title: Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease

doi: 10.1002/advs.202204717

Figure Lengend Snippet: Results of spatial‐temporal connected component analysis for the neurodegenerative brain regions in longitudinal AD sMRI images

Article Snippet: Plus, in the Supporting Information, the scatter diagram of P ‐score whole and AD (softmax) predictive score obtained by Ensemble 3DCNN for 638 AD sMRI images as shown in Table and Figure 2 was plotted to exhibit the association between P‐score at whole‐brain level and AD probability output from Ensemble 3DCNN , that is, AD (softmax) predictive scores, to some degree.

Techniques:

Illustration of the Ensemble 3DCNN . a) Image pre‐processing; b) Ensemble learning framework; c) Network architecture of each base classifier (3DCNN) .

Journal: Advanced Science

Article Title: Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease

doi: 10.1002/advs.202204717

Figure Lengend Snippet: Illustration of the Ensemble 3DCNN . a) Image pre‐processing; b) Ensemble learning framework; c) Network architecture of each base classifier (3DCNN) .

Article Snippet: Plus, in the Supporting Information, the scatter diagram of P ‐score whole and AD (softmax) predictive score obtained by Ensemble 3DCNN for 638 AD sMRI images as shown in Table and Figure 2 was plotted to exhibit the association between P‐score at whole‐brain level and AD probability output from Ensemble 3DCNN , that is, AD (softmax) predictive scores, to some degree.

Techniques:

Comparative results of the proposed models and other models used with different dataset.

Journal: Diagnostics

Article Title: A Two-Stage Framework for Automated Malignant Pulmonary Nodule Detection in CT Scans

doi: 10.3390/diagnostics10030131

Figure Lengend Snippet: Comparative results of the proposed models and other models used with different dataset.

Article Snippet: Vanilla 3DCNN , 70.5 , 59.3 , 76.1 , Kaggle.

Techniques: