We introduce a conditional implicit neural atlas (CINA) for spatio-temporal atlas generation from Magnetic Resonance Images (MRI) of the neurotypical and pathological fetal brain, that is fully independent of affine or non-rigid registration. During training, CINA learns a general representation of the fetal brain and encodes subject specific information into latent code. After training, CINA can construct a faithful atlas with tissue probability maps of the fetal brain for any gestational age (GA) and anatomical variation covered within the training domain. Thus, CINA is competent to represent both, neurotypical and pathological brains. Furthermore, a trained CINA model can be fit to brain MRI of unseen subjects via test-time optimization of the latent code. CINA can then produce probabilistic tissue maps tailored to a particular subject. We evaluate our method on a total of 198 T2 weighted MRI of normal and abnormal fetal brains from the dHCP and FeTA datasets. We demonstrate CINA's capability to represent a fetal brain atlas that can be flexibly conditioned on GA and on anatomical variations like ventricular volume or degree of cortical folding, making it a suitable tool for modeling both neurotypical and pathological brains. We quantify the fidelity of our atlas by means of tissue segmentation and age prediction and compare it to an established baseline. CINA demonstrates superior accuracy for neurotypical brains and pathological brains with ventriculomegaly. Moreover, CINA scores a mean absolute error of 0.23 weeks in fetal brain age prediction, further confirming an accurate representation of fetal brain development.

翻译：我们提出了一种条件隐式神经图谱（CINA），用于从正常发育和病理胎儿的磁共振图像（MRI）生成时空图谱，该方法完全独立于仿射或非刚性配准。在训练过程中，CINA学习胎儿脑的通用表征，并将受试者特定信息编码为潜在编码。训练完成后，CINA可为训练域覆盖范围内的任意胎龄（GA）和解剖变异构建具有组织概率图的精确胎儿脑图谱。因此，CINA既能表征正常发育脑也能表征病理脑。此外，训练好的CINA模型可通过测试时潜在编码优化来适配未见过受试者的脑MRI，进而生成针对特定个体的概率组织图。我们在来自dHCP和FeTA数据集的共198例正常及异常胎儿脑T2加权MRI上评估了该方法。我们证明了CINA能够灵活地根据胎龄、脑室体积或皮质折叠程度等解剖变异条件生成胎儿脑图谱，使其成为建模正常发育脑和病理脑的适用工具。我们通过组织分割和年龄预测定量评估了图谱的保真度，并与现有基线方法进行了比较。CINA在正常发育脑和伴有脑室扩大的病理脑上展示了卓越的准确性。此外，CINA在胎儿脑年龄预测中达到0.23周的平均绝对误差，进一步证实了对胎儿脑发育的精准表征。