TY - JOUR ID - 11932 TI - Measurement of the correlation coefficients between extracted features from CT and MR images JO - Iranian Journal of Medical Physics JA - IJMP LA - en SN - AU - Farhadi Birgani, Fariba AU - Fatehi, Daryoush AD - Department of Medical Physics, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran AD - Department of Medical Physics, Faculty of Medicine, Shahrekord University of Medical Sciences, Shahrekord, Iran. Y1 - 2018 PY - 2018 VL - 15 IS - Special Issue-12th. Iranian Congress of Medical Physics SP - 38 EP - 38 KW - CT-Scan KW - MRI KW - Image Feature KW - Correlation Coefficient DO - 10.22038/ijmp.2018.11932 N2 - Introduction: Nowadays applying computer in image processing is being improved revolutionary for solving medical images deficiencies. Image features that are analysis in image processing show image information. The aim of the present study was to find correlation between CT- scan and MRI images' features. Materials and Methods: After data acquisition, applying MATLAB image pre-processing and feature extract were performed for 1458 images of 6 patients (3 females and 3 males) referred to department of CT-scan & MRI of Golestan hospital (Ahwaz, Iran). Using SPSS the images' features were analyzed and correlation coefficients were calculated.   Results: There was significant relation between most of the features of the CT-scan images and the MRI (T1-weighted) images (p<0.01). The correlation coefficient between CT-scan images and MRI (T1-weighted) images was higher than those of CT-scan images and MRI (T2- weighted). Furthermore, the correlation coefficient between CT-scan images and MRI (T1- weighted) images was higher than those between MRI (T1-weighted) and MRI (T2- weighted) features' images. Maximum of the correlation coefficient was found between the texture features and its minimum was seen between the morphological features.   Conclusion: Conclusion: Although there is essential differences between physical basis of CT-scan and MRI as well as their clinical application, but there is a strong relationship between the extracted images' features of these twomedical diagnostic methods. UR - https://ijmp.mums.ac.ir/article_11932.html L1 - ER -