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Tibia

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Automated transtibial prosthesis alignment: A systematic review.

Artificial intelligence in medicine
This comprehensive systematic review critically analyzes the current progress and challenges in automating transtibial prosthesis alignment. The manual identification of alignment changes in prostheses has been found to lack reliability, necessitatin...

Development of an artificial intelligence model for predicting implant size in total knee arthroplasty using simple X-ray images.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate estimation of implant size before surgery is crucial in preparing for total knee arthroplasty. However, this task is time-consuming and labor-intensive. To alleviate this burden on surgeons, we developed a reliable artificial int...

Identification of footstrike pattern using accelerometry and machine learning.

Journal of biomechanics
Recent reports have suggested that there may be a relationship between footstrike pattern and overuse injury incidence and type. With the recent increase in wearable sensors, it is important to identify paradigms where the footstrike pattern can be d...

Evaluating the Effectiveness of Transtibial Prosthetic Socket Shape Design Using Artificial Intelligence: A Clinical Comparison With Traditional Plaster Cast Socket Designs.

Archives of physical medicine and rehabilitation
OBJECTIVE: To investigate the feasibility of creating an artificial intelligence (AI) algorithm to enhance prosthetic socket shapes for transtibial prostheses, aiming for a less operator-dependent, standardized approach.

Novel dilation-erosion labeling technique allows for rapid, accurate and adjustable alignment measurements in primary TKA.

Computers in biology and medicine
BACKGROUND: Optimal implant position and alignment remains a controversial, yet critical topic in primary total knee arthroplasty (TKA). Future study of ideal implant position will require the ability to efficiently measure component positions at sca...

Automatic Landmark Detection for Preoperative Planning of High Tibial Osteotomy Using Traditional Feature Extraction and Deep Learning Methods.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Automatic High Tibial Osteotomy (HTO) landmark detection methods promise to improve the effectiveness and standardisation of HTO preoperative planning. Unfortunately, due to the limited number of HTO datasets, existing methods are less ro...

Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVE: Longitudinal in vivo studies of murine xenograft models are widely utilized in oncology to study cancer biology and develop therapies. Magnetic resonance imaging (MRI) of these tumors is an invaluable tool for monitoring tumor g...

A robust deep learning approach for segmenting cortical and trabecular bone from 3D high resolution µCT scans of mouse bone.

Scientific reports
Recent advancements in deep learning have significantly enhanced the segmentation of high-resolution microcomputed tomography (µCT) bone scans. In this paper, we present the dual-branch attention-based hybrid network (DBAHNet), a deep learning archit...

Bone-wise rigid registration of femur, tibia, and fibula for the tracking of temporal changes.

Journal of applied clinical medical physics
BACKGROUND: Multiple myeloma (MM) induces temporal alterations in bone structure, such as osteolytic bone lesions, which are challenging to identify through manual image interpretation. The large variation in radiologists' assessments, even at expert...

Machine learning models for predicting tibial intramedullary nail length.

BMC musculoskeletal disorders
BACKGROUND: Tibial intramedullary nailing (IMN) represents a standard treatment for fractures of the tibial shaft. Nevertheless, accurately predicting the appropriate nail length prior to surgery remains a challenging endeavour. Conventional techniqu...