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EJNMMI Research

Table 1 The different sets of imaging feature combinations used as input to the approach

From: A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson’s disease

 

Feature set combinations

1

DaTscan + Semi-quantitative + All ImageNet

2

DaTscan + Semi-quantitative

3

DaTscan + All ImageNet

4

Semi-quantitative + All ImageNet

5

DaTscan

6

Semi-quantitative

7

All ImageNet

8

VGG16

9

ResNet50

10

DenseNet121

11

InceptionV3

  1. DaTscan imaging features refer to the imaging features extracted directly from the convolutional LSTM network. Semi-quantitative refers to the striatal binding ratio values from the right and left caudate nuclei and putamina
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