Affiliations:
Radiological Sciences Department, College of Applied Medical Sciences, Najran University, Najran, Saudi Arabia
Correspondence:
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Corresponding author: Khalaf Alshamrani, PhD Radiological Sciences Department, College of Applied Medical Sciences, Najran University, Najran, Saudi Arabia. E-mails: Kaalshamrani@hotmail.com and Kaalshamrani@nu.edu.sa.
Note: [1] This paper is published in the Special Issue of Medical Applications of X-Ray Imaging Techniques: Advances and Innovations. The Guest Editors are Dr. Malik Bader Alazzam (m.alazzam@aau.edu.jo) and Dr. Amita Nandal (nandalamita6@gmail.com).
Abstract: BACKGROUND:By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse PET and PET/CT images, is commonly used to evaluate lesions. OBJECTIVE:This study aims to build an image processing technique with the purpose of automatically detecting and isolating lesions in PET/CT images, as well as measuring and assessing the SUVmed. METHODS:The pictures are separated into their respective lesions using mathematical morphology and the crescent region, which are both part of the image processing method. In this research, a total of 18 different pictures of lesions were evaluated. RESULTS:The findings of the study reveal that the threshold is satisfied by both the SUVmax and the SUVmed for most of the lesion types. However, in six instances, the SUVmax and SUVmed values are found to be in different courts. CONCLUSION:The new information revealed by this study needs to be further investigated to determine if it has any practical value in diagnosing and monitoring lesions. However, results of this study suggest that SUVmed should receive more attention in the evaluation of lesions in PET and CT images.
