AIMC Topic: Anatomic Landmarks
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Fully automatic anatomical landmark localization and trajectory planning for navigated external ventricular drain placement.
Neurosurgical focus
Jul 1, 2025
OBJECTIVE: The aim of this study was to develop and validate a fully automatic anatomical landmark localization and trajectory planning method for external ventricular drain (EVD) placement using CT or MRI.
Central loss guides coordinated Transformer for reliable anatomical landmark detection.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Heatmap-based anatomical landmark detection is still facing two unresolved challenges: (1) inability to accurately evaluate the distribution of heatmap; (2) inability to effectively exploit global spatial structure information. To address the computa...
THERE: Toward an easy and reliable tool for automatic cephalometric analysis.
Computers in biology and medicine
Jun 1, 2025
BACKGROUND: Cephalometric analysis in orthodontics is a meticulous process requiring high precision in identifying anatomical landmarks on lateral cephalometric radiographs. Manual analysis by clinicians remains the standard, as even slight deviation...
Automatic assessment of lower limb deformities using high-resolution X-ray images.
BMC musculoskeletal disorders
May 27, 2025
BACKGROUND: Planning an osteotomy or arthroplasty surgery on a lower limb requires prior classification/identification of its deformities. The detection of skeletal landmarks and the calculation of angles required to identify the deformities are trad...
Comparison of individualized facial growth prediction models using artificial intelligence and partial least squares based on the Mathews growth collection.
The Angle orthodontist
May 1, 2025
OBJECTIVES: To develop facial growth prediction models using artificial intelligence (AI) under various conditions, and to compare performance of these models with each other as well as with the partial least squares (PLS) growth prediction model.
Assessment of the quality of different commercial providers using artificial intelligence for automated cephalometric analysis compared to human orthodontic experts.
Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie
May 1, 2025
PURPOSE: The aim of this investigation was to evaluate the accuracy of various skeletal and dental cephalometric parameters as produced by different commercial providers that make use of artificial intelligence (AI)-assisted automated cephalometric a...
Machine learning for automated identification of anatomical landmarks in ultrasound periodontal imaging.
Dento maxillo facial radiology
Mar 1, 2025
OBJECTIVES: To identify landmarks in ultrasound periodontal images and automate the image-based measurements of gingival recession (iGR), gingival height (iGH), and alveolar bone level (iABL) using machine learning.
The accuracy of automated facial landmarking - a comparative study between Cliniface software and patch-based Convoluted Neural Network algorithm.
European journal of orthodontics
Feb 7, 2025
BACKGROUND: Automatic landmarking software packages simplify the analysis of the 3D facial images. Their main deficiency is the limited accuracy of detecting landmarks for routine clinical applications. Cliniface is readily available open-access soft...
Patch-based convolutional neural networks for automatic landmark detection of 3D facial images in clinical settings.
European journal of orthodontics
Dec 1, 2024
BACKGROUND: The facial landmark annotation of 3D facial images is crucial in clinical orthodontics and orthognathic surgeries for accurate diagnosis and treatment planning. While manual landmarking has traditionally been the gold standard, it is labo...
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
Dec 1, 2024
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...
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