AIMC Topic: Anatomic Landmarks

Clear Filters Showing 91 to 100 of 133 articles

Integrating spatial configuration into heatmap regression based CNNs for landmark localization.

Medical image analysis Mar 25, 2019
In many medical image analysis applications, only a limited amount of training data is available due to the costs of image acquisition and the large manual annotation effort required from experts. Training recent state-of-the-art machine learning met...
Hand Anatomic Landmarks Cephalometry Spine Humans Neural Networks, Computer Tomography, X-Ray Computed Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging
View on PubMed DOI

Fully automated radiological analysis of spinal disorders and deformities: a deep learning approach.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Mar 12, 2019
PURPOSE: We present an automated method for extracting anatomical parameters from biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions, including sagittal and coronal deformities, degenerative phenomena as well ...
Humans Neural Networks, Computer Anatomic Landmarks Spine Hip Joint Deep Learning Spinal Curvatures Models, Statistical Radiography
View on PubMed DOI

Automatic 3D cephalometric annotation system using shadowed 2D image-based machine learning.

Physics in medicine and biology Feb 20, 2019
This paper presents a new approach to automatic three-dimensional (3D) cephalometric annotation for diagnosis, surgical planning, and treatment evaluation. There has long been considerable demand for automated cephalometric landmarking, since manual ...
Humans Machine Learning Anatomic Landmarks Reproducibility of Results Cephalometry Imaging, Three-Dimensional Automation
View on PubMed DOI

Evaluating reinforcement learning agents for anatomical landmark detection.

Medical image analysis Feb 14, 2019
Automatic detection of anatomical landmarks is an important step for a wide range of applications in medical image analysis. Manual annotation of landmarks is a tedious task and prone to observer errors. In this paper, we evaluate novel deep reinforc...
Pregnancy Female Adult Humans Brain Anatomic Landmarks Heart Head Deep Learning Imaging, Three-Dimensional Magnetic Resonance Imaging
View on PubMed DOI

Deep Geodesic Learning for Segmentation and Anatomical Landmarking.

IEEE transactions on medical imaging Oct 12, 2018
In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmarking. Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identificatio...
Craniofacial Abnormalities Adolescent Child Cone-Beam Computed Tomography Mandible Anatomic Landmarks Image Interpretation, Computer-Assisted Adult Male Deep Learning Algorithms Female Young Adult Humans
View on PubMed DOI

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.

IEEE transactions on bio-medical engineering Sep 12, 2018
In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlate...
Male Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Female Humans Anatomic Landmarks Aged Algorithms Alzheimer Disease Aged, 80 and over Brain
View on PubMed DOI

Predictive connectome subnetwork extraction with anatomical and connectivity priors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Aug 25, 2018
We present a new method to identify anatomical subnetworks of the human connectome that are optimally predictive of targeted clinical variables, developmental outcomes or disease states. Given a training set of structural or functional brain networks...
Magnetic Resonance Imaging Predictive Value of Tests Anatomic Landmarks Autistic Disorder Infant, Premature Connectome Humans Machine Learning Infant, Newborn
View on PubMed DOI

Neural multi-atlas label fusion: Application to cardiac MR images.

Medical image analysis Jul 31, 2018
Multi-atlas segmentation approach is one of the most widely-used image segmentation techniques in biomedical applications. There are two major challenges in this category of methods, i.e., atlas selection and label fusion. In this paper, we propose a...
Image Enhancement Heart Ventricles Image Interpretation, Computer-Assisted Pattern Recognition, Automated Humans Algorithms Neural Networks, Computer Magnetic Resonance Imaging Anatomic Landmarks
View on PubMed DOI

Weakly-supervised convolutional neural networks for multimodal image registration.

Medical image analysis Jul 4, 2018
One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a method to infer voxel-level transformation from higher-level correspo...
Anatomic Landmarks Humans Prostatic Neoplasms Neural Networks, Computer Imaging, Three-Dimensional Prostate Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Male Ultrasonography
View on PubMed DOI

Towards intelligent robust detection of anatomical structures in incomplete volumetric data.

Medical image analysis Jun 23, 2018
Robust and fast detection of anatomical structures represents an important component of medical image analysis technologies. Current solutions for anatomy detection are based on machine learning, and are generally driven by suboptimal and exhaustive ...
Anatomic Landmarks Humans Deep Learning Algorithms Imaging, Three-Dimensional Tomography, X-Ray Computed Image Processing, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals