北京生物醫(yī)學(xué)工程

基于Demons的微分同胚非剛性配準(zhǔn)研究

Diffeomorphic Nonrigid Image Registration Based on Demons Algorithm

作者：徐挺劉偉李傳富馮煥清

單位：中國(guó)科學(xué)技術(shù)大學(xué)電子科學(xué)與技術(shù)系（合肥230027）

關(guān)鍵詞：非剛性配準(zhǔn)；微分同胚；指數(shù)映射；優(yōu)化

分類號(hào)：

出版年·卷·期（頁(yè)碼）：2010·29·1（49-54）

摘要：

Demons算法的一個(gè)局限是它無(wú)法處理大形變，且不能產(chǎn)生微分同胚的變換以滿足計(jì)算解剖學(xué)的形態(tài)分析需要。利用李群中的指數(shù)映射，把原來(lái)Demons形變場(chǎng)相加的更新方式改進(jìn)為若干次形變場(chǎng)間的復(fù)合，同時(shí)又保證了較高的運(yùn)算效率。實(shí)驗(yàn)表明，新算法能配準(zhǔn)大形變問(wèn)題，且真實(shí)顱腦CT的實(shí)驗(yàn)結(jié)果與Demons算法的結(jié)果相近，但產(chǎn)生的形變場(chǎng)光滑可逆，并有相對(duì)更小的形變能量。

One of the limitations of the Demons algorithm is that it can neither handle large deformation nor generate diffeomorphic spatial transformations which are required for the shape analysis in the framework of Computational Anatomy. We proposed to replace the addition of freeform deformation in the Demons’ update step by a few compositions of deformation fields using group exponential. The algorithm proved to be computationally efficient. Our experiments showed that this new algorithm was capable of recovering large deformation and is diffeomorphic with similar results of the Demons algorithm. The generated deformation were smooth and invertible in terms of Jacobian with much lower energy of the deformation fields.

參考文獻(xiàn)：

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