AIMC Topic: Head

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A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images.

Medical image analysis Oct 14, 2022
Cancer region detection (CRD) and subtyping are two fundamental tasks in digital pathology image analysis. The development of data-driven models for CRD and subtyping on whole-slide images (WSIs) would mitigate the burden of pathologists and improve ...
Supervised Machine Learning Head Neoplasms Humans
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Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR.

PloS one Oct 12, 2022
The segmentation of medical and dental images is a fundamental step in automated clinical decision support systems. It supports the entire clinical workflow from diagnosis, therapy planning, intervention, and follow-up. In this paper, we propose a no...
Head Cone-Beam Computed Tomography Radionuclide Imaging Image Processing, Computer-Assisted Artificial Intelligence Skull
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BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources.

Zeitschrift fur medizinische Physik Sep 2, 2022
INTRODUCTION: Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brains containing significant susceptibility sources, such as intracranial...
Brain Mapping Head Magnetic Resonance Imaging Brain Humans Algorithms Image Processing, Computer-Assisted Deep Learning
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Anisotropic SpiralNet for 3D Shape Completion and Denoising.

Sensors (Basel, Switzerland) Aug 27, 2022
Three-dimensional mesh post-processing is an important task because low-precision hardware and a poor capture environment will inevitably lead to unordered point clouds with unwanted noise and holes that should be suitably corrected while preserving ...
Artifacts Head Neural Networks, Computer Anisotropy
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Inter-Slice Resolution Improvement Using Convolutional Neural Network with Orbital Bone Edge-Aware in Facial CT Images.

Journal of digital imaging Aug 22, 2022
The 3D modeling of orbital bones in facial CT images is essential to provide a customized implant for reconstructions of orbit and related structures during surgery. However, 3D models of the orbital bone show an aliasing effect and disconnected thin...
Neural Networks, Computer Tomography, X-Ray Computed Humans Head Orbit
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The contribution of object identity and configuration to scene representation in convolutional neural networks.

PloS one Jun 28, 2022
Scene perception involves extracting the identities of the objects comprising a scene in conjunction with their configuration (the spatial layout of the objects in the scene). How object identity and configuration information is weighted during scene...
Neural Networks, Computer Humans Head Brain
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Automatic head computed tomography image noise quantification with deep learning.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jun 4, 2022
PURPOSE: Computed tomography (CT) image noise is usually determined by standard deviation (SD) of pixel values from uniform image regions. This study investigates how deep learning (DL) could be applied in head CT image noise estimation.
Deep Learning Humans Head Neural Networks, Computer Image Processing, Computer-Assisted Tomography, X-Ray Computed
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Automated soccer head impact exposure tracking using video and deep learning.

Scientific reports Jun 3, 2022
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact expo...
Video Recording Football Soccer Head Deep Learning Brain Injuries Humans
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Age Estimation of Faces in Videos Using Head Pose Estimation and Convolutional Neural Networks.

Sensors (Basel, Switzerland) May 31, 2022
Age estimation from human faces is an important yet challenging task in computer vision because of the large differences between physical age and apparent age. Due to the differences including races, genders, and other factors, the performance of a l...
Head Male Neural Networks, Computer Humans Female
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Efficient fetal ultrasound image segmentation for automatic head circumference measurement using a lightweight deep convolutional neural network.

Medical physics May 24, 2022
PURPOSE: Fetal head circumference (HC) is an important biometric parameter that can be used to assess fetal development in obstetric clinical practice. Most of the existing methods use deep neural network to accomplish the task of automatic fetal HC ...
Pregnancy Neural Networks, Computer Image Processing, Computer-Assisted Female Humans Head
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