eprintid: 10192642 rev_number: 7 eprint_status: archive userid: 699 dir: disk0/10/19/26/42 datestamp: 2024-05-21 13:39:41 lastmod: 2024-05-21 13:39:41 status_changed: 2024-05-21 13:39:41 type: article metadata_visibility: show sword_depositor: 699 creators_name: Zhang, Xuechen creators_name: Cheng, Isaac creators_name: Jin, Yingzhao creators_name: Shi, Jiandong creators_name: Li, Chenrui creators_name: Xue, Jing-Hao creators_name: Tam, Lai-Shan creators_name: Yu, Weichuan title: DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images ispublished: pub divisions: UCL divisions: B04 divisions: C06 divisions: F61 keywords: Elastic Riemannian metric; Statistical shape analysis; Applied differential geometry; Inflammatory rheumatic disease; Bone proliferation analysis note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Bone proliferation is an important pathological feature of inflammatory rheumatic diseases. Although recent advance in high-resolution peripheral quantitative computed tomography (HR-pQCT) enables physicians to study microarchitectures, physicians' annotation of proliferation suffers from slice inconsistency and subjective variations. Also, there are only few effective automatic or semi-automatic tools for proliferation detection. In this study, by integrating pathological knowledge of proliferation formation with the advancement of statistical shape analysis theory, we present an unsupervised method, named Deformation-Controllable Elastic Shape model, for 3D bone Proliferation Analysis (DCES-PA). Unlike previous shape analysis methods that directly regularize the smoothness of the displacement field, DCES-PA regularizes the first and second-order derivative of the displacement field and decomposes these vector fields according to different deformations. For the first-order elastic metric, DCES-PA orthogonally decomposes the first-order derivative of the displacement field by shearing, scaling and bending deformation, and then penalize deformations triggering proliferation formation. For the second-order elastic metric, DCES-PA encodes both intrinsic and extrinsic surface curvatures into the second-order derivative of the displacement field to control the generation of high-curvature regions. By integrating the elastic shape metric with the varifold distances, DCES-PA achieves correspondence-free shape analysis. Extensive experiments on both simulated and real clinical datasets demonstrate that DCES-PA not only shows an improved accuracy than other state-of-the-art shape-based methods applied to proliferation analysis but also produces highly sensitive proliferation annotations to assist physicians in proliferation analysis. date: 2024-06 date_type: published publisher: Elsevier official_url: http://dx.doi.org/10.1016/j.compbiomed.2024.108533 full_text_type: other language: eng verified: verified_manual elements_id: 2274000 doi: 10.1016/j.compbiomed.2024.108533 medium: Print-Electronic pii: S0010-4825(24)00617-6 lyricists_name: Xue, Jinghao lyricists_id: JXUEX60 actors_name: Xue, Jinghao actors_id: JXUEX60 actors_role: owner full_text_status: restricted publication: Computers in Biology and Medicine volume: 175 article_number: 108533 event_location: United States issn: 0010-4825 citation: Zhang, Xuechen; Cheng, Isaac; Jin, Yingzhao; Shi, Jiandong; Li, Chenrui; Xue, Jing-Hao; Tam, Lai-Shan; Zhang, Xuechen; Cheng, Isaac; Jin, Yingzhao; Shi, Jiandong; Li, Chenrui; Xue, Jing-Hao; Tam, Lai-Shan; Yu, Weichuan; - view fewer <#> (2024) DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images. Computers in Biology and Medicine , 175 , Article 108533. 10.1016/j.compbiomed.2024.108533 <https://doi.org/10.1016/j.compbiomed.2024.108533>. document_url: https://discovery.ucl.ac.uk/id/eprint/10192642/1/CIBM-XuechenZhang-2024.pdf