Trên cơ sở các kết quả mà luận án đã đạt được, nội dung nghiên cứu của luận án có thể được tiếp tục nghiên cứu và phát triển theo các hướng sau
- Nghiên cứu, phát triển giải pháp hỗ trợ chẩn đoán vùng chứa tổn
thương hình khối là ác tính hay lành tính
- Nghiên cứu, phát triển giải pháp hỗ trợ phát hiện vùng chứa tổn
DANH MỤC CÁC CÔNG TRÌNH CÔNG BỐ CỦA LUẬN ÁN [1]. Nguyen Viet Dung, Nguyen Duc Thuan, Nguyen Tien Dzung, Pham
Van Thanh, An Automated Method to Segment and Classify Masses in Mammograms, International Journal of Electrical and Computer Engineering vol 4(8), 2009, ISSN: 2010-3956.
[2]. Viet Dzung Nguyen, Duc Thuan Nguyen, Tien Dzung Nguyen, Thom Thao Nguyen Thi, Duc Hoa Tran, A Program For Locating Possible Breast Masses On Mammograms, Third International Conference on Biomedical Engineering in Vietnam, 2010
[3]. Nguyen Viet Dung, Pham Van Thanh, Nguyen Tien Dung, Nguyen Duc Thuan, Automatically contour-based detection of suspicious massive lesions in mammograms, Journal of Science and Technology, No. 79B, 2010, ISSN: 0868-3980
[4]. Viet Dzung Nguyen, Duc Thuan Nguyen, Tien Dzung Nguyen, Huu Long Nguyen, Duc Huyen Bui, Application of Neural Network in Classifying Massive Lesions in Mammogram, The 4th International Conference on Biomedical Engineering in Vietnam, 2012
[5]. Viet Dzung Nguyen, Duc Thuan Nguyen, Huu Long Nguyen, Duc Huyen Bui, Tien Dzung Nguyen, Automatic identification of massive lesions in digitalized mammograms, The Fourth International Conference on Communications and Electronics (ICCE2012), Vietnam, 2012
[6]. Q. D. Truong, M. P. Nguyen, V. T. Hoang, H. T. Nguyen, D. T. Nguyen, T. D. Nguyen, V. D. Nguyen, Feature Extraction and Support Vector Machine Based Classification for False Positive Reduction in Mammographic Images, Springer Lecture Notes in Electrical Engineering, vol. 269, 2013, ISSN: 1876-1100
[7]. M. P. Nguyen, Q. D. Truong, D. T. Nguyen, T. D. Nguyen, V. D. Nguyen, An Alternative Approach to Reduce Massive False Positives in Mammograms Using Block Variance of Local Coefficients Features and Support Vector Machine, Elsevier Procedia of Computer Science, Vol. 20, 2013, ISSN: 1877-0509.
[8]. V. D. Nguyen, D. T. Nguyen, T. D. Nguyen, Q. D. Truong, M. D. Le,
Combination of Block Difference Inverse Probability Features and Support Vector Machine to Reduce False Positives in Computer-Aided Detection for Massive Lesions in Mammographic Images, The 6th International Conference on Biomedical Engineering and Informatics (BMEI2013), China, 2013