Earticle

초록

영어

Medical images constitute a substantial portion of all medical data, but various issues arise, including noise and judgment-related problems. Therefore, recent research has actively explored deep learning applications, such as noise removal and disease classification based on medical images. In particular, brain tumors are typically diagnosed using MRI, and early detection is crucial. In this study, the classification of MRI images for brain tumor patients was conducted by improving MRI noise and utilizing a pre-trained CNN model.

목차

Abstract
I. INTRODUCTION
II. METHOD
A. Dataset & Image Preprocessing
B. MRI Data quality management
C. Brain Tumor Prediction
III. RESULT
A. Image Quality Measure
B. Brain tumor Prediction
IV. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• Kyoungsu Oh [ Dept. of Computer Engineering Gachon University ]
• Seok-hwan Kang [ Dept. of Computer Engineering Gachon University ]
• Suehyun Lee [ Dept. of Computer Engineering Gachon University ]
• Hyekyung Woo [ Dept.of Health Administration Kongju National University ]
• Youngho Lee [ Dept. of Computer Engineering Gachon University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004