xviii

List of Figures

4.4

Various thresholding techniques were applied on same brain

MRI images. The source image featured in this figure was se-

lected from the dataset available as open source on Kaggle [5].

125

4.5

Adaptive thresholding techniques were applied on same brain

MRI images. The source image featured in this figure was se-

lected from the dataset available as open source on Kaggle [5].

127

4.6

Edge-based techniques were applied on same brain MRI images.

The source image featured in this figure was selected from the

dataset available as open source on Kaggle [5].

. . . . . . . .

132

4.7

Clustering based techniques were applied on same brain MRI

images. The source image featured in this figure was selected

from the dataset available as open source on Kaggle [5]. . . .

134

5.1

Illustration of some Scalar Indices at an axial slice. . . . . . .

150

5.2

WM/none-WM classifications of brain tissues using k-means.

151

5.3

CSF/none-CSF classifications of brain tissues using k-means.

151

5.4

Sample simulation of primary Glioma growth. . . . . . . . . .

152

5.5

Tumor growth simulation using R1 with different diffusion

methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

153

5.6

Tumor growth simulation using R2 with different diffusion

methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

153

5.7

Tumor growth simulation using R3 with different diffusion

methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

154

8.1

A simplified A. Microarray B. RNA-seq workflow. . . . . . .

200

8.2

Total number of experiments in the GEO repository for brain

diseases and disorders and total number of genes associated

with the studied diseases and disorders from the DisGeNET

database (As of August 2023). . . . . . . . . . . . . . . . . . .

203

9.1

Functional brain network construction. . . . . . . . . . . . . .

227

9.2

A sample graph to evaluate graph analysis parameters. . . . .

228

9.3

a Erdos-Renyi Network, b Watts-Strogats Network.

. . . . .

232

9.4

a Barabasi-Albert Network 20 nodes, b Barabasi-Albert Net-

work 40 nodes.

. . . . . . . . . . . . . . . . . . . . . . . . . .

232

9.5

Modules and hubs. Modules are shown in dotted regions, central

hubs are in black and gateway hubs are in gray. . . . . . . . .

233

9.6

Some motifs of three nodes found in brain networks. . . . . .

236

10.1 A typical workflow of MS-based proteomics. . . . . . . . . . .

254

10.2 An overview of proteomics methods and applications.

. . . .

255