Determination of ۶۸Ga-DOTA-FAPI and ۱۸FDG PET/CT Imaging inLiver Metastases Patients Diagnosis with Chaotic Deep Neural Network

Malignant liver cancer is the main causes of death all over the world and its incidencerate is increasing every year. According to World Health Organization (WHO) data, liver cancercauses about ۸۳۰,۰۰۰ deaths which is the third leading reason of cancer deaths in ۲۰۲۰-۲۲. Manystudies represented early detection of liver cancer that can help to improve survival rates. However,the symptoms of liver cancer are not apparent, so most patients with liver cancer in the early stagesare already in the middle and late stages at the time of diagnosis, in other senences, the treatmentoptions for them are limited. These factors make liver cancer have a terrible prognosis. Therefore,proposing a method that can effectively perform early detection and help improve the outcome ofliver cancer treatment is great practical importance. This article uses some filters for noise reductionand then use Chaotic Deep Neural Networks (ChDNN) methods for segmentation which optimizedand tuned by a Genetic Algorithm. We use PET/CT imaging performed with ۶۸Ga-DOTA-FAPI and۱۸FDG to diagnosis liver metastases patients. Obtained results represented exact area of nodulesdetection in images.

Keywords:

Liver Cancer , Image Segmentation , Chaotic Deep Neural Networks (ChDNN) , Deep Learning , Genetic Algorithm