| One of the mathematical based techniques used for processing
the medical images in order to identify the irregularity properties
of these images is employing different types of Image processing
algorithms. Detecting these abnormalities in terms of their risk of
malignancy such as tumors in thyroid gland is of a major
importance in nuclear medicine which is known as cold nodules.
In this study, the radioisotope image of thyroid gland is used for
extracting the cold nodules based on hot nodule extraction. For
this purpose, two routes are employed which will be unified later
for nodule extraction through a simple intelligent system. At First,
the gray level of blue channel of the target image is mapped from
range of [0,1] to [1,0] that a portion of the resulted image will be
selected according to a predefined threshold. Second, the color
image will be transformed into gray scale which will be then
enhanced by circular average filtering and highlighting the
intensity methods. Moreover, thresholding stage will also be
applied to the obtained image in the second approach. After all
both resulted images will be added and mapped will be then from
range of [0,1] to [1,0]which will be ready for feature extraction
using the simple hill climbing methodology. The results showed
that after executing the process for hundred times the best area
for cold nodule will be identified with high accuracy. In
conclusion, it has been shown that by using image processing
technique along with a simple intelligent system such as hill
climbing algorithm, one can achieve the highest performance (i.e.,
accuracy of 0.9896) in detecting the malignancy in several
medical related images |