Scholarlink

Breast cancer is a prevalent malignant tumor worldwide, and early detection is essential for successful treatment and recovery. Medical image analysis algorithm has become one of the most concerned issues in the field of breast cancer diagnosis. However, it is difficult to improve detection accuracy because of data insufficient and model performance. In this paper, magnetic resonance imaging (MRI) images are processed by Histogram equalization and data augmentation. And YOLOv8 is adopted to detect breast cancer. Result shows the detection accuracy was improved with the use of the proposed method. It obtained an average accuracy of 88.25%, superior to those of YOLOv7, YOLOv5, and Faster-RCNN. That can provide a feasibility study for the practical application of computer-aided diagnosis.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Research on Breast Cancer Diagnosis Based on Deep Learning and Medical Image Processing

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Shuhua Li,
  • Mary Jane C. Samonte,
  • Fenglong Yan

摘要

Breast cancer is a prevalent malignant tumor worldwide, and early detection is essential for successful treatment and recovery. Medical image analysis algorithm has become one of the most concerned issues in the field of breast cancer diagnosis. However, it is difficult to improve detection accuracy because of data insufficient and model performance. In this paper, magnetic resonance imaging (MRI) images are processed by Histogram equalization and data augmentation. And YOLOv8 is adopted to detect breast cancer. Result shows the detection accuracy was improved with the use of the proposed method. It obtained an average accuracy of 88.25%, superior to those of YOLOv7, YOLOv5, and Faster-RCNN. That can provide a feasibility study for the practical application of computer-aided diagnosis.