Preparation of Your Submission for the ۳rd International Congress for Radiology StudentsThe Impact of Computer Vision in Enhancing Ovarian Tumor Detection

Background: Detection of ovarian tumors is crucial for early diagnosis and treatment, which in turn improves patients' overall survival rate. Conventional methods for tumor detection typically involve manual interpretation of medical images, resulting in subjective and time-consuming evaluations. Methods: Recent advancements in computer vision techniques have transformed the field of medical imaging by automating the detection process and enhancing accuracy.Results: The use of computer vision techniques has shown promising results in the analysis of ovarian tumors. These techniques have the ability to extract quantitative picture information that cannot be detected by the human eye. This provides a more accurate evaluation of the tumor compared to traditional methods [۱-۳].Conclusions: Picture feature extraction applying radiomics or deep learning (DL) has demonstrated promising results in tumour analysis and can provide quantitative picture information that is invisible by human eyes, in contrast to subjective radiological imaging evaluation by humans [۲-۱۲].