bibtext: @InProceedings{ Zha_Implicit_MICCAI2024,
                   author = { Zhang, Minghui and Zhang, Hanxiao and You, Xin and Yang, Guang-Zhong and Gu, Yun },
                   title = { { Implicit Representation Embraces Challenging Attributes of Pulmonary Airway Tree Structures } },
                   booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
                   year = {2024},
                   publisher = {Springer Nature Switzerland},
                   volume = { LNCS 15001 },
                   month = {October},
                   pages = { pending },
                }
abstract: High-ﬁdelity modeling of the pulmonary airway tree from CT scans is critical to preoperative planning. However, the granularity of CT scan resolutions and the intricate topologies limit the accuracy of manual or deep-learning-based delineation of airway structures, resulting in coarse representation accompanied by spike-like noises and disconnectivity issues. To address these challenges, we introduce a Deep Geometric Correspondence Implicit (DGCI) network that implicitly models airway tree structures in the continuous space rather than discrete voxel grids. DGCI ﬁrst explores the intrinsic topological features shared within diﬀerent airway cases on top of implicit neural representation(INR). Speciﬁcally, we establish a reversible correspondence ﬂow to constrain the feature space of training shapes. Moreover, implicit geometric regularization is utilized to promote a smooth and high-ﬁdelity representation of ﬁne-scaled airway structures. By transcending voxel-based representation, DGCI acquires topological insights and integrates geometric regularization into INR, generating airway tree structures with state-of-the-art topological ﬁdelity. Detailed evaluation results on the public dataset demonstrated the superiority of the DGCI in the scalable delineation of airways and downstream applications. Source codes can be found at: https://github.com/EndoluminalSurgicalVision-IMR/DGCI.
title: Implicit Representation Embraces Challenging Attributes of Pulmonary Airway Tree Structures
authors: Zhang, Minghui Zhang, Hanxiao You, Xin Yang, Guang-Zhong Gu, Yun