AIMC Topic: Anatomic Landmarks

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Diagnostic performance of fetal intelligent navigation echocardiography (FINE) in fetuses with double-outlet right ventricle (DORV).

The international journal of cardiovascular imaging Jul 8, 2020
The main objective of this study was to investigate the diagnostic performance of FINE in generating and displaying 3 specific abnormal fetal echocardiography views such as left ventricular outflow tract (LVOT) view, right ventricular outflow tract (...
Ultrasonography, Prenatal Spatio-Temporal Analysis Diagnosis, Computer-Assisted Reproducibility of Results Young Adult Adult Gestational Age Humans Double Outlet Right Ventricle Artificial Intelligence Fetal Heart Pregnancy Echocardiography, Four-Dimensional Female Predictive Value of Tests Anatomic Landmarks Image Interpretation, Computer-Assisted
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Automatic Midline Identification in Transverse 2-D Ultrasound Images of the Spine.

Ultrasound in medicine & biology Jul 7, 2020
Effective epidural needle placement and injection involves accurate identification of the midline of the spine. Ultrasound, as a safe pre-procedural imaging modality, is suitable for epidural guidance because it offers adequate visibility of the vert...
Anatomic Landmarks Epidural Space Humans Neural Networks, Computer Ultrasonography
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Web-based fully automated cephalometric analysis by deep learning.

Computer methods and programs in biomedicine May 6, 2020
BACKGROUND AND OBJECTIVE: An accurate lateral cephalometric analysis is vital in orthodontic diagnosis. Identification of anatomic landmarks on lateral cephalograms is tedious, and errors may occur depending on the doctor's experience. Several attemp...
Deep Learning Radiography Anatomic Landmarks Cephalometry Internet
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Learning-based local-to-global landmark annotation for automatic 3D cephalometry.

Physics in medicine and biology Apr 23, 2020
The annotation of three-dimensional (3D) cephalometric landmarks in 3D computerized tomography (CT) has become an essential part of cephalometric analysis, which is used for diagnosis, surgical planning, and treatment evaluation. The automation of 3D...
Tomography, X-Ray Computed Reproducibility of Results Imaging, Three-Dimensional Humans Machine Learning Skull Anatomic Landmarks Cephalometry Automation
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Development of an artificial intelligence system using deep learning to indicate anatomical landmarks during laparoscopic cholecystectomy.

Surgical endoscopy Apr 18, 2020
BACKGROUND: The occurrence of bile duct injury (BDI) during laparoscopic cholecystectomy (LC) is an important medical issue. Expert surgeons prevent intraoperative BDI by identifying four landmarks. The present study aimed to develop a system that ou...
Cholecystectomy, Laparoscopic Humans Artificial Intelligence Algorithms Deep Learning Anatomic Landmarks
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Fully automatic segmentation of glottis and vocal folds in endoscopic laryngeal high-speed videos using a deep Convolutional LSTM Network.

PloS one Feb 10, 2020
The objective investigation of the dynamic properties of vocal fold vibrations demands the recording and further quantitative analysis of laryngeal high-speed video (HSV). Quantification of the vocal fold vibration patterns requires as a first step t...
Glottis Databases as Topic Vocal Cords Larynx Anatomic Landmarks Video Recording Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Female Adult Endoscopy Time Factors Humans
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HeadLocNet: Deep convolutional neural networks for accurate classification and multi-landmark localization of head CTs.

Medical image analysis Jan 28, 2020
Cochlear implants (CIs) are used to treat subjects with hearing loss. In a CI surgery, an electrode array is inserted into the cochlea to stimulate auditory nerves. After surgery, CIs need to be programmed. Studies have shown that the cochlea-electro...
Humans Neural Networks, Computer Tomography, X-Ray Computed Cochlear Implantation Imaging, Three-Dimensional Ear, Inner Image Processing, Computer-Assisted Anatomic Landmarks
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Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.

Clinical breast cancer Dec 5, 2019
BACKGROUND: Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to de...
Fluorodeoxyglucose F18 Sentinel Lymph Node Radiopharmaceuticals Positron-Emission Tomography Datasets as Topic Reproducibility of Results Breast Neoplasms Axilla Humans Image Processing, Computer-Assisted ROC Curve Anatomic Landmarks Neural Networks, Computer Female Lymphatic Metastasis Feasibility Studies Magnetic Resonance Imaging
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Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization.

Medical image analysis Nov 23, 2019
Cone-beam computed tomography (CBCT) scans are commonly used in diagnosing and planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities. Based on CBCT images, it is clinically essential to generate an accurate 3D mo...
Image Processing, Computer-Assisted Anatomic Landmarks Maxillofacial Abnormalities Neural Networks, Computer Humans Cone-Beam Computed Tomography Imaging, Three-Dimensional
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Partial Policy-Based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images.

IEEE transactions on medical imaging Oct 9, 2019
Utilizing the idea of long-term cumulative return, reinforcement learning (RL) has shown remarkable performance in various fields. We follow the formulation of landmark localization in 3D medical images as an RL problem. Whereas value-based methods h...
Humans Spine Aorta Imaging, Three-Dimensional Magnetic Resonance Imaging Machine Learning Anatomic Landmarks Algorithms Tomography, X-Ray Computed
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