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- W2097304855 abstract "A brain anatomical image sequence obtained through histology posed a new challenge to medical image registration. Aligning hundreds to thousands of image slices using a pairwise registration technique may cause error propagation or introduce random error. Information across multiple adjacent image slices must be considered for the alignment. We developed a new similarity metric called minimum entropy of bad prediction (MEBP) that is suitable for pairwise image registration and image sequence alignment (ISA). MEBP is intensity-based, but it outperforms almost all other intensity-based metrics. When MEBP is used in ISA, it scales very well. MEBP has been applied to a rabbit brain digital atlas construction, and it is applicable to many similar problems." @default.
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- W2097304855 date "2005-04-12" @default.
- W2097304855 modified "2023-10-17" @default.
- W2097304855 title "An extendable registration similarity metric for anatomical image sequence alignment" @default.
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- W2097304855 doi "https://doi.org/10.1109/isbi.2004.1398643" @default.
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