Results 181 to 190 of about 46,141 (262)

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features

Orthopaedic Surgery, Volume 17, Issue 5, Page 1513-1524, May 2025.
This study developed an automated distal radius fracture classification system based on statistical shape model (SSM) feature extraction and neural network classification. The method first extracts point cloud data from CT images, then extracts fracture features through registration, downsampling, and PCA dimensionality reduction, before inputting them
Xing‐bo Cai, Ze‐hui Lu, Zhi Peng, Yong‐qing Xu, Jun‐shen Huang, Hao‐tian Luo, Yu Zhao, Zhong‐qi Lou, Zi‐qi Shen, Zhang‐cong Chen, Xiong‐gang Yang, Ying Wu, Sheng Lu   +12 more
wiley   +1 more source

Anatomy-Weighted CTDIvol from Routine CT Metadata: A Patient-Specific, Multi-Vendor Study Using Deep-Learning Segmentation. [PDF]

Tomography
Yamamoto S.
europepmc   +1 more source

Percutaneous Vertebroplasty for Painful Osteoporotic Vertebral Compression Fractures: A Retrospective Comparative Study of a Negative Pressure‐Guided Technique

Orthopaedic Surgery, EarlyView.
In 60 patients with vertebral compression fractures, negative‐pressure‐guided vertebroplasty (NPVP) promoted more uniform cement distribution and reduced cement leakage compared with conventional PVP, resulting in greater perioperative safety and improved radiographic and clinical outcomes at 3 months.
Botao Zhang, Zihan Wang, Shibing Zhang, Zhipeng Xi, Xin Chen, Qingyuan Ru, Ke Wu, Rongrong Deng, Xin Liu, Ran Kang   +9 more
wiley   +1 more source

Report on the 2025 DICOM WSI Connectathon. [PDF]

J Pathol Inform
Clunie DA, Napora B, Groth J, Zerbe N, Yousif M, Shelar G, Sárga T, Borman S, Cheng C, Plewa P, Silva LB, Birmingham R, Philbrick K, Pellikka M, Preston R, Tata L, Anderson D, Yang F, Fedorov A, Patel S, Kwon J, Knapp M, Usrey T, Tena FJC, Madrigal E, Wang D, Lien CY, Collins L, Somers A, Saxena A, Martin E, Hussain M, Cram P, Doré J, Carreira F.   +34 more
europepmc   +1 more source

Three‐dimensional digital quantitative analysis of periodontal and peri‐implant phenotype—A narrative review

Periodontology 2000, EarlyView.
Abstract 3D digital evaluation of the periodontal and peri‐implant tissue, including CBCT, intraoral scanning, optical surface scanning, and ultrasonography, is being used in the clinical arena with increasing frequency. Thus, to validate the utilization of 3D digital analysis for this purpose, a critical evaluation of the reliability of digital ...
Yi Te Lin, Chenshuang Li, Jonathan Korostoff, Joseph P. Fiorellini, Jie Yang, Yu‐Cheng Chang   +5 more
wiley   +1 more source

Reproducibility of fetal global longitudinal strain measured with speckle tracking echocardiography using a fixed cardiac cycle. [PDF]

PLoS One
Meireson E, de Vet C, van Laar JOEH, Mussche P, Roelens K, van Oostrum NHM.   +5 more
europepmc   +1 more source

Long‐term stability of transcrestal sinus augmentation

Periodontology 2000, EarlyView.
Abstract Transcrestal sinus augmentation has emerged as a minimally invasive alternative to lateral window techniques for vertical bone augmentation in the edentulous maxilla. Since its early introduction and modification over the last several decades, this technique has demonstrated predictable outcomes for implant placement in regions with limited ...
Sandra H. Stuhr, Muhammad H. A. Saleh, Tiziano Testori, Hom‐Lay Wang, Ann M. Decker   +4 more
wiley   +1 more source

Associations of static anatomical geometry with planned dosimetric endpoints in prostate radiotherapy: a multicenter study. [PDF]

Front Oncol
Lin W, Fang Y, Chen Y, Liang C, Li Z, Lin X, Fang J, Chen J, Xiao L.   +8 more
europepmc   +1 more source

Guiding the AI revolution in periodontology and implant dentistry: Concepts, ethics, accountability, and a roadmap for sustainable adoption

Periodontology 2000, EarlyView.
Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali, Negin Soghli, Patricia A. Miguez   +2 more
wiley   +1 more source

MHub.ai: A Standardized Platform for Reproducible AI Research in Medical Imaging

Aerts H, Nürnberg L, Bontempi D, Pai S, Lisle C, Pieper S, Kikinis R, de Leemput Sv, Soni R, Murugesan G, Ciausu C, Groeneveld M, Dorfner F, Jiang J, Rangnekar A, Veeraraghavan H, Bosma J, Bressem K, Mak R, Fedorov A.   +19 more
europepmc   +1 more source