Contrast-Enhanced Ultrasound and Magnetic Resonance Enhancement Based on Machine Learning in Cancer Diagnosis in the Context of the Internet of Things Medical System.

Abstract

As an accurate, safe, and effective noninvasive examination method, imaging examination has been widely used in the diagnosis and differential diagnosis of focal liver lesions. Enhanced ultrasonography (CEUS), enhanced CT (CECT), and enhanced magnetic resonance imaging (CEMRI) are the most commonly used enhanced imaging methods in clinical practice, all of which can accurately determine the nature of liver lesions. The purpose of this paper is to study the application of contrast-enhanced ultrasound and magnetic resonance enhancement in cancer diagnosis based on the Internet of Things medical system. The basic clinical data, CEUS, and enhanced CT/MRI findings of 120 CHC patients were retrospectively analyzed. The clinicopathological features of CHC patients were investigated by contrast-enhanced ultrasonography and CT/MRI enhanced mode. The diagnostic value of contrast-enhanced ultrasound and enhanced CT/MRI combined with tumor markers in CHC was analyzed. The experimental results showed that the sensitivities of CEUS, enhanced MRI, and their combination in diagnosing CHC were 72.44%, 81.56%, and 93.78%, respectively. This experiment has an important value in the diagnosis of primary liver cancer.