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Table 2 Datasets

From: Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

Datasets

Description

Features

Synthetic brain MRI images

10 slices (109 × 131 comprising 5589 pixels), 6 noise levels (0%, 1%, 3%, 5%, 7%, 9%) 3 RF inhomogeneity levels (0%, 20%, 40%)

Haralick (14)

Prostate MRI images

16 slices, 2 datasets (256 × 256 comprising 15,000-40,000 pixels)

Haralick, 1st order statistical (38)

Gene-Expression data:

  

Prostate Tumor

102 training, 34 testing, 12,600 genes

 

Breast Cancer Relapse

78 training, 19 testing, 24,481 genes

300 most class-

Lymphoma

38 training, 34 testing, 7130 genes

informative genes

Lung Cancer

32 training, 149 testing, 12,533 genes

 
  1. Image and gene-expression datasets used in our experiments.