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:

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:

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:

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: