AIMC Topic: Anatomic Landmarks

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Preciseness of artificial intelligence for lateral cephalometric measurements.

Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie Mar 9, 2023
BACKGROUND: The aim of the study was to assess the accuracy and efficiency of a new artificial intelligence (AI) method in performing lateral cephalometric radiographic measurements.
Artificial Intelligence Software Algorithms Humans Cephalometry Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Anatomic Landmarks
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Automatic 3-Dimensional Cephalometric Landmarking via Deep Learning.

Journal of dental research Aug 18, 2022
The increasing use of 3-dimensional (3D) imaging by orthodontists and maxillofacial surgeons to assess complex dentofacial deformities and plan orthognathic surgeries implies a critical need for 3D cephalometric analysis. Although promising methods w...
Cephalometry Retrospective Studies Reproducibility of Results Deep Learning Imaging, Three-Dimensional Anatomic Landmarks
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Accuracy of auto-identification of the posteroanterior cephalometric landmarks using cascade convolution neural network algorithm and cephalometric images of different quality from nationwide multiple centers.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Jan 21, 2022
INTRODUCTION: The purpose of this study was to evaluate the accuracy of auto-identification of the posteroanterior (PA) cephalometric landmarks using the cascade convolution neural network (CNN) algorithm and PA cephalogram images of a different qual...
Humans Cephalometry Reproducibility of Results Radiography Neural Networks, Computer Anatomic Landmarks Algorithms
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Automatic localization of cephalometric landmarks based on convolutional neural network.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Nov 18, 2021
INTRODUCTION: Cephalometry plays an important role in the diagnosis and treatment of orthodontics and orthognathic surgery. This study intends to develop an automatic landmark location system to make cephalometry more convenient.
Humans Neural Networks, Computer Cephalometry Orthodontics Reproducibility of Results Radiography Anatomic Landmarks
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Machine learning approach to needle insertion site identification for spinal anesthesia in obese patients.

BMC anesthesiology Oct 18, 2021
BACKGROUND: Ultrasonography for neuraxial anesthesia is increasingly being used to identify spinal structures and the identification of correct point of needle insertion to improve procedural success, in particular in obesity. We developed an ultraso...
Anesthesia, Obstetrical Lumbar Vertebrae Anesthesia, Spinal Young Adult Adult Cohort Studies Obesity Anatomic Landmarks Ultrasonography, Interventional Humans Pregnancy Female Cesarean Section Machine Learning Algorithms
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Accuracy of automated identification of lateral cephalometric landmarks using cascade convolutional neural networks on lateral cephalograms from nationwide multi-centres.

Orthodontics & craniofacial research Jun 27, 2021
OBJECTIVE: To investigate the accuracy of automated identification of cephalometric landmarks using the cascade convolutional neural networks (CNN) on lateral cephalograms acquired from nationwide multi-centres.
Neural Networks, Computer Humans Anatomic Landmarks Reproducibility of Results Cephalometry Radiography
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Structure-Coherent Deep Feature Learning for Robust Face Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jun 2, 2021
In this paper, we propose a structure-coherent deep feature learning method for face alignment. Unlike most existing face alignment methods which overlook the facial structure cues, we explicitly exploit the relation among facial landmarks to make th...
Humans Automated Facial Recognition Face Databases, Factual Deep Learning Anatomic Landmarks
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Identifying anatomical structures on ultrasound: assistive artificial intelligence in ultrasound-guided regional anesthesia.

Clinical anatomy (New York, N.Y.) May 11, 2021
Ultrasound-guided regional anesthesia involves visualizing sono-anatomy to guide needle insertion and the perineural injection of local anesthetic. Anatomical knowledge and recognition of anatomical structures on ultrasound are known to be imperfect ...
Humans Anatomic Landmarks Artificial Intelligence Ultrasonography, Interventional Clinical Competence Anesthetics, Local
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Automatic Cephalometric Landmark Identification System Based on the Multi-Stage Convolutional Neural Networks with CBCT Combination Images.

Sensors (Basel, Switzerland) Jan 12, 2021
This study was designed to develop and verify a fully automated cephalometry landmark identification system, based on multi-stage convolutional neural networks (CNNs) architecture, using a combination dataset. In this research, we trained and tested ...
Humans Imaging, Three-Dimensional Anatomic Landmarks Cephalometry Craniofacial Abnormalities Retrospective Studies Neural Networks, Computer Reproducibility of Results Databases, Factual Cone-Beam Computed Tomography
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Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.

Journal of vascular surgery Dec 9, 2020
OBJECTIVE: Imaging software has become critical tools in the diagnosis and decision making for the treatment of abdominal aortic aneurysms (AAA). However, the interobserver reproducibility of the maximum cross-section diameter is poor. This study aim...
Software Design Aortography Multidetector Computed Tomography Computed Tomography Angiography Aortic Aneurysm, Abdominal Reproducibility of Results Workflow Deep Learning Humans Anatomic Landmarks Observer Variation Predictive Value of Tests Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Automation
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