Breast Cancer Classification Prediction Based on Ultrasonic Image Feature Recognition

Exploring an effective method to manage the complex breast cancer clinical information and selecting a suitable classifier for predictive modeling still require continuous research and verification in the actual clinical environment. This paper combines the ultrasound image feature algorithm to construct a breast cancer classification model. Furthermore, it combines the motion process of the ultrasound probe to accurately connect the ultrasound probe to the breast tumor. Moreover, this paper constructs a hardware and software system structure through machine vision algorithms and intelligent motion algorithms. Furthermore, it combines coordinate transformation and image recognition algorithms to expand the recognition process to realize automatic and intelligent real-time breast cancer diagnosis. In addition, this paper combines machine learning algorithms to process data and obtain an intelligent system model. Finally, this paper designs experiments to verify the intelligent system of this paper. Through experimental research, it can be seen that the breast cancer classification prediction system based on ultrasonic image feature recognition has certain effects.