AIMC Topic: Anatomic Landmarks

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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...
Algorithms Deep Learning Anatomic Landmarks Cholecystectomy, Laparoscopic Humans Artificial Intelligence
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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...
Databases as Topic Neural Networks, Computer Anatomic Landmarks Humans Glottis Algorithms Adult Vocal Cords Video Recording Female Larynx Image Interpretation, Computer-Assisted Endoscopy Time Factors
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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 Ear, Inner Imaging, Three-Dimensional 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 Axilla Image Processing, Computer-Assisted Reproducibility of Results Humans Datasets as Topic Lymphatic Metastasis Breast Neoplasms Anatomic Landmarks Neural Networks, Computer Magnetic Resonance Imaging ROC Curve Feasibility Studies Female
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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...
Neural Networks, Computer Cone-Beam Computed Tomography Imaging, Three-Dimensional Humans Image Processing, Computer-Assisted Anatomic Landmarks Maxillofacial Abnormalities
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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...
Spine Aorta Machine Learning Algorithms Tomography, X-Ray Computed Imaging, Three-Dimensional Magnetic Resonance Imaging Humans Anatomic Landmarks
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Hubless keypoint-based 3D deformable groupwise registration.

Medical image analysis Sep 24, 2019
We present a novel algorithm for Fast Registration Of image Groups (FROG), applied to large 3D image groups. Our approach extracts 3D SURF keypoints from images, computes matched pairs of keypoints and registers the group by minimizing pair distances...
Image Interpretation, Computer-Assisted Humans Artificial Intelligence Algorithms Imaging, Three-Dimensional Anatomic Landmarks Benchmarking
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Automated vertebrae localization and identification by decision forests and image-based refinement on real-world CT data.

La Radiologia medica Sep 14, 2019
PURPOSE: Development of a fully automatic algorithm for the automatic localization and identification of vertebral bodies in computed tomography (CT).
Algorithms Retrospective Studies Aged Adult Middle Aged Aged, 80 and over Young Adult Humans Machine Learning Datasets as Topic Decision Trees Anatomic Landmarks Multidetector Computed Tomography Spine
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Accurate automated Cobb angles estimation using multi-view extrapolation net.

Medical image analysis Aug 9, 2019
Accurate automated quantitative Cobb angle estimation that quantitatively evaluates scoliosis plays an important role in scoliosis diagnosis and treatment. It solves the problem of the traditional manual method, which is the current clinical standard...
Datasets as Topic Image Enhancement Scoliosis Child Anatomic Landmarks Radiographic Image Interpretation, Computer-Assisted Humans Deep Learning
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Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network.

Medical image analysis Jul 19, 2019
Grading spondylolisthesis into several stages from MRI images is challenging because detecting critical vertebrae and locating landmarks in images of different characteristics is difficult. We propose Faster Adversarial Recognition (FAR) network to a...
Spondylolisthesis Humans Anatomic Landmarks Image Interpretation, Computer-Assisted Neural Networks, Computer Pattern Recognition, Automated Severity of Illness Index Magnetic Resonance Imaging
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