AIMC Topic: Image Processing, Computer-Assisted

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Large scale simulation of labeled intraoperative scenes in unity.

International journal of computer assisted radiology and surgery
PURPOSE: The use of synthetic or simulated data has the potential to greatly improve the availability and volume of training data for image guided surgery and other medical applications, where access to real-life training data is limited.

Improving Image Quality for Single-Angle Plane Wave Ultrasound Imaging With Convolutional Neural Network Beamformer.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrafast ultrasound imaging based on plane wave (PW) compounding has been proposed for use in various clinical and preclinical applications, including shear wave imaging and super resolution blood flow imaging. Because the image quality afforded by ...

MCAL: An Anatomical Knowledge Learning Model for Myocardial Segmentation in 2-D Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Segmentation of the left ventricular (LV) myocardium in 2-D echocardiography is essential for clinical decision making, especially in geometry measurement and index computation. However, segmenting the myocardium is a time-consuming process and chall...

A Lightweight Convolutional Neural Network Model for Liver Segmentation in Medical Diagnosis.

Computational intelligence and neuroscience
Liver segmentation and recognition from computed tomography (CT) images is a warm topic in image processing which is helpful for doctors and practitioners. Currently, many deep learning methods are used for liver segmentation that takes a long time t...

Real-Time Tracking of Object Melting Based on Enhanced DeepLab 3+ Network.

Computational intelligence and neuroscience
In order to reveal the dissolution behavior of iron tailings in blast furnace slag, the main component of iron tailings, SiO, was used for research. Aiming at the problem of information loss and inaccurate extraction of tracking molten SiO particles ...

Toward Exploiting Second-Order Feature Statistics for Arbitrary Image Style Transfer.

Sensors (Basel, Switzerland)
Generating images of artistic style from input images, also known as image style transfer, has been improved in the quality of output style and the speed of image generation since deep neural networks have been applied in the field of computer vision...

Automatic MRI segmentation of pectoralis major muscle using deep learning.

Scientific reports
To develop and validate a deep convolutional neural network (CNN) method capable of selecting the greatest Pectoralis Major Cross-Sectional Area (PMM-CSA) and automatically segmenting PMM on an axial Magnetic Resonance Imaging (MRI). We hypothesized ...

H-SegNet: hybrid segmentation network for lung segmentation in chest radiographs using mask region-based convolutional neural network and adaptive closed polyline searching method.

Physics in medicine and biology
Chest x-ray (CXR) is one of the most commonly used imaging techniques for the detection and diagnosis of pulmonary diseases. One critical component in many computer-aided systems, for either detection or diagnosis in digital CXR, is the accurate segm...

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

Magnetic resonance in medicine
PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan.

An improved YOLO Nano model for dorsal hand vein detection system.

Medical & biological engineering & computing
To date, venipuncture, the most necessary and fundamental medical means, still remains a challenging task for medical stuff due to significant individual differences in vein condition. Thanks to mature development in near-infrared (NIR) imaging techn...