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Anatomic Landmarks

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A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation.

IEEE journal of translational engineering in health and medicine
To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommodating the complex anatomy and significant variations, optimizing surgical approaches, reducing postoperative complications, and preserving liver func...

A machine learning approach for age prediction based on trigeminal landmarks.

Journal of forensic and legal medicine
OBJECTIVE: The aim of this study was to estimate the chronological age (CA) of a growing individual using a new machine learning approach on Cone Beam Computed Tomography (CBCT).

Automatic point detection on cephalograms using convolutional neural networks: A two-step method.

Dental materials journal
This project aimed to develop an artificial intelligence program tailored for cephalometric images. The program employs a convolutional neural network with 6 convolutional layers and 2 affine layers. It identifies 18 key points on the skull to comput...

Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods.

The Angle orthodontist
OBJECTIVES: To evaluate an artificial intelligence (AI) model in predicting soft tissue and alveolar bone changes following orthodontic treatment and compare the predictive performance of the AI model with conventional prediction models.

Artificial intelligence for orthodontic diagnosis and treatment planning: A scoping review.

Journal of dentistry
OBJECTIVES: To provide an overview of artificial intelligence (AI) applications in orthodontic diagnosis and treatment planning, and to evaluate whether AI improves accuracy, reliability, and time efficiency compared to expert-based manual approaches...

Evaluation of the clinical utility of lateral cephalometry reconstructed from computed tomography extracted by artificial intelligence.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
This study assessed the accuracy and reliability of artificial intelligence (AI)-reconstructed images of two-dimensional (2D) lateral cephalometric analyses of facial computed tomography (CT) images, which is widely used for the diagnosis of craniofa...

Patch-based convolutional neural networks for automatic landmark detection of 3D facial images in clinical settings.

European journal of orthodontics
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
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...

AI-based open-source software for cephalometric analysis from limited FOV radiographs.

Journal of dentistry
BACKGROUND: Artificial Intelligence (AI) in dental diagnostics is evolving, offering innovative approaches for conducting cephalometric analysis with less manual input and overcoming the limitations of traditional imaging methods. To enhance the diag...