Medical Image Processing of Para Nasal Sinus and Nasal Cavity from Cone-Beam CT Images by Using Micro-Array Algorithm (MAA)

EasyChair Preprint no. 7381

Abstract

Abstract Background and objectives: This paper produces a new method of para-nasal sinuses and nasal cavity image processing by Microarray algorithm. Malignancy can occur in any of the cells, that line mucosa. Every variety of malignancy differs based upon its growth and behavior. We examined the accumulation paranasal sinuses and nasal cavity image a better segmentation will make easier to read and identify the cavity by the expert physician Methods: Nasal Cavity and Para nasal image results are difficult to considerable from the different types of image modalities by expert surgeon. In order to get both qualitative and quantitative results, we has been developed a system for diagnosis of paranasal sinus and nasal cavity using MAA algorithm. Results: The modalities images of paranasal sinus and nasal cavity are segmented using looping method of Microarray (MAA) algorithm to extract the each pixel in means of extracellular components of an image. The segmentation is the one of the main process of the system uses microarray conversion to a single pixel of image using Principal Component Analysis (PCA) that has highest bright then normalize the actual image to the array range. Conclusion: Segmentation of paranasal sinuses and nasal cavity has more advantages, that with less mental risk easily diagnosis the problem by respective physician reduces the time spending with specialists and decreases the intra and inter observer differences.

Keyphrases: analysis, MAA Algorithms, Micro-array, Paranasal sinuses, Thresholding

@Booklet{EasyChair:7381,
  author = {H Ali Abdul Rahman and M Talal Aljeraisi},
  title = {Medical Image Processing of Para Nasal Sinus and Nasal Cavity from Cone-Beam CT Images by Using Micro-Array Algorithm (MAA)},
  howpublished = {EasyChair Preprint no. 7381},

  year = {EasyChair, 2022}}