AIMC Topic: Image Processing, Computer-Assisted

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Diversity-Sensitive Generative Adversarial Network for Terrain Mapping Under Limited Human Intervention.

IEEE transactions on cybernetics
In a collaborative air-ground robotic system, the large-scale terrain mapping using aerial images is important for the ground robot to plan a globally optimal path. However, it is a challenging task in a novel and dynamic field without historical hum...

MR spectroscopy frequency and phase correction using convolutional neural networks.

Magnetic resonance in medicine
PURPOSE: To introduce a novel convolutional neural network (CNN)-based approach for frequency-and-phase correction (FPC) of MR spectroscopy (MRS) spectra to achieve fast and accurate FPC of single-voxel MEGA-PRESS MRS data.

Image-Based Artificial Intelligence in Wound Assessment: A Systematic Review.

Advances in wound care
Accurately predicting wound healing trajectories is difficult for wound care clinicians due to the complex and dynamic processes involved in wound healing. Wound care teams capture images of wounds during clinical visits generating big datasets over...

Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To study the diagnostic effect of 64-slice spiral CT and MRI high-resolution images based on deep convolutional neural networks(CNN) in lung cancer.

NeuroGen: Activation optimized image synthesis for discovery neuroscience.

NeuroImage
Functional MRI (fMRI) is a powerful technique that has allowed us to characterize visual cortex responses to stimuli, yet such experiments are by nature constructed based on a priori hypotheses, limited to the set of images presented to the individua...

Brain tissue segmentation via non-local fuzzy c-means clustering combined with Markov random field.

Mathematical biosciences and engineering : MBE
The segmentation and extraction of brain tissue in magnetic resonance imaging (MRI) is a meaningful task because it provides a diagnosis and treatment basis for observing brain tissue development, delineating lesions, and planning surgery. However, M...

Imaging Manifestations and Evaluation of Postoperative Complications of Bone and Joint Infections under Deep Learning.

Journal of healthcare engineering
To explore and evaluate the imaging manifestations of postoperative complications of bone and joint infections based on deep learning, a retrospective study was performed on 40 patients with bone and joint infections in the Department of Orthopedics ...

TypeSeg: A type-aware encoder-decoder network for multi-type ultrasound images co-segmentation.

Computer methods and programs in biomedicine
PURPOSE: As a portable and radiation-free imaging modality, ultrasound can be easily used to image various types of tissue structures. It is important to develop a method which supports the multi-type ultrasound images co-segmentation. However, state...

Multi-scale Selection and Multi-channel Fusion Model for Pancreas Segmentation Using Adversarial Deep Convolutional Nets.

Journal of digital imaging
Organ segmentation from existing imaging is vital to the medical image analysis and disease diagnosis. However, the boundary shapes and area sizes of the target region tend to be diverse and flexible. And the frequent applications of pooling operatio...

Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.

Nutrients
Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for diet...