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Biomedical subjects

Wu-Fan Chen

Publications and source records attributed to Wu-Fan Chen.

3 recordsLinked to original sources

Elastic registration of medical images through multiquadric method.

OBJECTIVE: To improve the precision and reliability of elastic registration of the medical images and to simplify the registration process. METHODS: Previous study concerning elastic registration mostly focused on manual selection of the landmarks and then use of adequate interpolating for elastic transformation. The landmarks extraction, however, was prone to error that often showed impact on the registration results, besides the difficulty and time consumption of manual identification of the landmarks. On the basis of Multiquadric method that allowed smooth adjustment of the parameters, we utilized a semi-automatic method to extract the landmarks by combining these 2 steps, and proposed a novel registration method. RESULTS: Using this method for medical image elastic registration, rapid and accurate registration between standard and deformed images was achieved. CONCLUSION: The method proposed presently is accurate, convenient and reliable.

Automation↗

A method for three-dimensional surface reconstruction of volume data field.

OBJECTIVE: To explore a novel method of three-dimensional (3D) reconstruction based on vector field smoothing, for the purpose of 3D surface reconstruction of DICOM format volume data sets. METHODS: 3D external surface of three sets of volume data, namely craniocerebral volume data, pelvis volume data, and rat embryo volume data, were respectively extracted by Marching Cubes algorithm using small triangle flakes to approach the original 3D structure surfaces. Vector field smoothing was performed on the extracted 3D surfaces. The reconstructed 3D structures were rendered from different angles of view through arbitrary rotation. RESULTS: High-quality results of 3D surface reconstruction were obtained for each set of volume data, demonstrating fine 3D surface details and high fidelity. CONCLUSION: This method can improve 3D surface reconstruction from DICOM volume data sets, promising high quality, fidelity and reality.

Animals↗

Automatic segmentation of cardiac magnetic resonance images using knowledge base.

OBJECTIVE: To study the automated implementation of cardiac magnetic resonance image (MRI) segmentation. METHODS: By training the feature parameters of the images and establishing a knowledge base, an efficient method for extracting and using prior knowledge was proposed. RESULTS and CONCLUSION: Through extracting and using prior knowledge of cardiac MRI, automation of cardiac MRI segmentation can be well accomplished.

Journal Article↗