Radiomics: Extracting more Features using Endoscopic Imaging

Presentation summary
Topics
Computer Aided detection systems
What is “Radiomics”?
Computed Tomography images
Conclusion
Descusion
Endoscopic images

Computer Aided detection systems

Radiomics refers to the conversion of images into mineable information and also the analyze that information for decision support.
What is Radiomics?
Histogram analysis
Texture Feature
Color Based feature
Shape Based features
Mean
median
maximum intensity
minimum intensity
1- Contrast
2- Correlation
3- Spectral
4- Homogeneity
Color Histogram
Histogram Intersection
Color Histogram for K means
Color Correlogram
Chromaticity
Perimeter of the Boundary
Diameter of Boundary
Eccentricity
Curvature
Topological Descriptors

CT images are overcome the matter of superimposition of organs, bones, and another parts of body in any depths, by taking many images of the region of interest with variety angles.
Computed Tomography images
Advantages
Limits
CT IMAGING
detect mucosal tissues and nodules
easier to make difference between the bones of the back and front side
The applied radiations to the body in CT scans
CT Scan represents data at a particular point of time

Endoscopy is a technic to make medical image through the endoscope and a camera at the end of the scope connected to a larger monitor.
Endoscopic images
Advantages
Limits
Endoscopic IMAGING
provides direct and clear field visualization of the disease.
endoscopy is a minimally invasive procedure
endoscopy cannot make images from inside of muscles
depth perception is not possible with endoscopes

In medical specialty, features of cancers detected from radiological data (e.g. CT scans, endoscopy images and MRI) are often use to process detection, prediction, and prognostic cancer in patient.
Discussion
CT Images
Endoscopic Images
Histogram analysis
Texture Feature
Shape Based features
Color Based feature
HSV color histogram
(Hue, Saturation, Value)
RG (Red Green) Texture
LBP texture
(Local Binary Pattern)

Conclusion
According to the features extracted from the medical images reviewed in this Presentation, endoscopic images are capable of extracting color features that significantly improve the performance of the cancer detection system.
However, due to the limitations of the use of endoscopic imaging, which cannot detect diseases that are primarily involve the submucosa, muscular, or serosal layers of the intestine also, if suspected that the bowel is punctured, it is not a good procedure, endoscopic images cannot be used to detect all types of cancers. Thus, if endoscopic and CT scan images are available, the processing of endoscopic images will increase the efficiency of cancer detection as compared with CT scan.