Design and manufacturing of personalized implants and standardized templates for cranioplasty applications
Thiết kế và chế tạo mảnh ghép cá thể hoá và khuôn mẫu chuẩn hoá cho ứng dụng tạo hình hộp sọ
Tác giả
Le Chi Hieu, E. Bohez, J. Vander Sloten, H.N. Phien, V. Esichaikul, P.H. Binh, P.V. An, N.C. To, P. Oris
Tên thành viên BIRALAB được in đậm và liên kết tới trang cá nhân.
Tóm tắt
Cranial (skull) defects are treated by the cranioplasty technique, which is required to protect underlying brain, correct major aesthetic deformities, or both. This research was aimed at investigating the technical solutions for cranioplasty treatments for the ASEAN countries based on available production and material technologies in this region. Solutions for design and manufacturing of personalized cranioplasty implants and a new concept of standardized templates (SDTs) for cranioplasty applications are presented. SDTs are made in mass production, based on the reverse engineering and rapid tooling techniques; they are used for preparing cranioplasty implants both pre- and intra-operatively. With the development of the design support database and program interfacing between the Medical Image Processing (MIP) and Computer Aided Design (CAD) system, the design time for the personalized cranioplasty implant was minimized to half a day. Through the use of SDTs, surgeons have a new solution to prepare implants in which the required skills are reduced. The cost of implants made by proposed solutions is acceptable for the ASEAN region.
Lĩnh vực liên quan
Công bố liên quan
- Báo cáo hội nghị2026
Machine Learning and Statistical Approach for Thyroid Cancer Detection
Tiếp cận kết hợp học máy và thống kê trong phát hiện ung thư tuyến giáp
Nguyen Thu Huyen, Nguyen Thi Yen Nhi, Ngo Phuong Minh, Nguyen Thuy Tien, Tran Anh Vu, Hoang Quang Huy, Pham Thi Viet Huong
Proceedings of the Fifth International Conference on Intelligent Systems and Networks, 283-292
- Bài báo tạp chí2026
Multichannel Learning Framework for Enhanced ECG Signal Classification Using Wavelet and MFCCs Features
Khung học đa kênh nâng cao độ chính xác phân loại tín hiệu điện tim dựa trên đặc trưng wavelet và hệ số MFCC
Tran Anh Vu, Mai Tat Chuyen, Nguyen Thi Diem Anh, Hoang Quang Huy, Pham Thi Viet Huong
Iranian Journal of Science and Technology, Transactions of Electrical Engineering
- Báo cáo hội nghị2025
A Hybrid 1D-CNN and Transformer Architecture for Differentiating Malignant Melanoma from Non-Melanoma Skin Cancers using Raman Spectroscopy
Kiến trúc lai ghép 1D-CNN và Transformer phân biệt u hắc tố ác tính với ung thư da không hắc tố bằng quang phổ Raman
Chu Duc Hoang, Nguyen Thanh Tung
2025 International Conference on Advanced Technologies for Communications (ATC), 1-6

