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In this paper, we establish a novel framework for automatic landmark detection and registration of brain cortical surfaces using quasi-conformal geometry and convolutional neural networks. We propose
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Computers in biology refers to the application of computational techniques and tools to analyze and interpret biological data, facilitating research and discoveries in areas such as genomics, proteomics, and systems biology.
Researchers, scientists, and organizations involved in biological research and data analysis are typically required to file this information, especially in compliance with regulatory and funding requirements.
To fill out computers in biology, one should gather relevant biological data, utilize appropriate computational tools and software, and ensure compliance with established guidelines and protocols for reporting.
The purpose of computers in biology is to enhance the analysis of complex biological data, improve the accuracy of biological modeling, and facilitate data sharing and collaboration within the scientific community.
Information that must be reported includes data types, methodologies used, analysis results, software tools employed, and any relevant findings that contribute to the understanding of biological processes.
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