Attention-Based Point Cloud Completion for CT-Equivalent Kidney Volumetry from Tracked Freehand Ultrasound.

Sikai Ge, Wuwei Ma, Hao Tang, Menglin Wu, Shanshan Wang, Junwei Wu, Fei Ma, Xuejun Shang

Abstract read

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Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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8 authors.

Sikai GeDepartment of Urology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.ORCID http://orcid.org/0009-0002-8770-8265

Wuwei MaSchool of Computer Science and Information Engineering, Changzhou Institute of Technology, Changzhou, China.

Hao TangDepartment of Urology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.

Menglin WuSchool of Computer and Information Engineering, Nanjing Tech University, Nanjing, 211816, China.

Shanshan WangCarbon Medical Device Ltd., Shenzhen, 518000, China.

Junwei WuSchool of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China.

Fei MaSchool of Mathematics and Physics, Xi'an Jiaotong-Liverpool University, Suzhou, China. fei.ma@xjtlu.edu.cn.

Xuejun ShangDepartment of Urology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China. shangxj98@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney volume measurement is critical for managing polycystic kidney disease and monitoring transplants, but computed tomography involves radiation and conventional ultrasound has 20-30% error. This study validates tracked freehand ultrasound with attention-based point cloud completion for kidney volumetry, with the primary objective of determining equivalence to computed tomography within a ± 2% margin. Sixty healthy volunteers (30 male, 30 female; mean age 44 years; enrolled March-August 2024; 120 kidneys) undergoing routine health examination computed tomography underwent electromagnetic-tracked ultrasound using three standardized scanning maneuvers and same-day computed tomography. Sparse point clouds from ultrasound were completed using an attention-based transformer network (PointAttN) and four benchmark architectures. Volumes were compared against computed tomography using equivalence testing on per-kidney relative differences within a ± 2% margin. Tracked freehand ultrasound achieved mean absolute error of 3.94 mL (3.0% relative error) in multiaxis merged mode and passed statistical equivalence testing (TOST: p

Indexed as

Attention mechanismDeep learningFreehand ultrasoundKidney volumetryPoint cloud completion

Identifiers

PMID42162524

DOI10.1016/j.cosrev.2025.100831

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.