@article{article_436897, title={3D Mass Visualization of Thyroid CT Images thru Marching Cubes Method}, journal={Electronic Letters on Science and Engineering}, volume={14}, pages={20–26}, year={2018}, url={https://izlik.org/JA48US56FF}, author={Yurttakal, Ahmet Haşim and Erbay, Hasan and İkizceli, Türkan and Karaçavuş, Seyhan and Çınarer, Gökalp}, keywords={Computed Tomography (CT),Marching Cubes Algorithms,Hounsfield Unit (HU)}, abstract={<pre style="text-align:justify;background:#FFFFFF;"> Thyroid cancer is the type of cancer caused by the cells of the thyroid gland. This is less common than other types of cancer. If the correct diagnosis is made and appropriate treatment is given, the disease can be completely removed. </pre> <pre style="text-align:justify;background:#FFFFFF;"> </pre> <pre style="text-align:justify;background:#FFFFFF;"> Herein, we present an algorithm to 3D visualize thyroid cancer using 2D Dicom images. As is known, Dicom is the de-facto file standard in medical imaging, and these files contain useful metadata as well. We use some of these meta-attributes to calculate the Hounsfield Unit. In other words, the pixel values are calculated according to the average attenuation of the tissue corresponding to a scale of -1024 to + 3071 on the Hounsfield scale. Dicom images used in the study were obtained from patients under the supervision of specialist doctors. Thyroid cancer tumors were modelled in 3D using the pixel values thru Marching Cubes Algorithm. </pre> }, number={3}