Skip to main content

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.