AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Phantoms, Imaging

Showing 471 to 480 of 748 articles

Clear Filters

Deep learning-based reconstruction of ultrasound images from raw channel data.

International journal of computer assisted radiology and surgery
PURPOSE: We investigate the feasibility of reconstructing ultrasound images directly from raw channel data using a deep learning network. Starting from the raw data, we present the network the full measurement information, allowing for a more generic...

The effects of different levels of realism on the training of CNNs with only synthetic images for the semantic segmentation of robotic instruments in a head phantom.

International journal of computer assisted radiology and surgery
PURPOSE: The manual generation of training data for the semantic segmentation of medical images using deep neural networks is a time-consuming and error-prone task. In this paper, we investigate the effect of different levels of realism on the traini...

Ultrasound Deep Learning for Wall Segmentation and Near-Wall Blood Flow Measurement.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Studies of medical flow imaging have technical limitations for accurate analysis of blood flow dynamics and vessel wall interaction at arteries. We propose a new deep learning-based boundary detection and compensation (DL-BDC) technique in ultrasound...

Fast and accurate calculation of myocardial T and T values using deep learning Bloch equation simulations (DeepBLESS).

Magnetic resonance in medicine
PURPOSE: To propose and evaluate a deep learning model for rapid and accurate calculation of myocardial T /T values based on a previously proposed Bloch equation simulation with slice profile correction (BLESSPC) method.

Photoacoustic Imaging to Track Magnetic-manipulated Micro-Robots in Deep Tissue.

Sensors (Basel, Switzerland)
The next generation of intelligent robotic systems has been envisioned as micro-scale mobile and externally controllable robots. Visualization of such small size microrobots to track their motion in nontransparent medium such as human tissue remains ...

Denoising of multi b-value diffusion-weighted MR images using deep image prior.

Physics in medicine and biology
The clinical value of multiple b-value diffusion-weighted (DW) magnetic resonance imaging (MRI) has been shown in many studies. However, DW-MRI often suffers from low signal-to-noise ratio, especially at high b-values. To address this limitation, we ...

AirNet: Fused analytical and iterative reconstruction with deep neural network regularization for sparse-data CT.

Medical physics
PURPOSE: Sparse-data computed tomography (CT) frequently occurs, such as breast tomosynthesis, C-arm CT, on-board four-dimensional cone-beam CT (4D CBCT), and industrial CT. However, sparse-data image reconstruction remains challenging due to highly ...

High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Biomedical physics & engineering express
Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-...

Leveraging vision and kinematics data to improve realism of biomechanic soft tissue simulation for robotic surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical simulations play an increasingly important role in surgeon education and developing algorithms that enable robots to perform surgical subtasks. To model anatomy, finite element method (FEM) simulations have been held as the gold sta...

Error detection using a convolutional neural network with dose difference maps in patient-specific quality assurance for volumetric modulated arc therapy.

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)
The aim of this study was to evaluate the use of dose difference maps with a convolutional neural network (CNN) to detect multi-leaf collimator (MLC) positional errors in patient-specific quality assurance for volumetric modulated radiation therapy (...