AIMC Topic: Image Processing, Computer-Assisted

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Combined tract segmentation and orientation mapping for bundle-specific tractography.

Medical image analysis
While the major white matter tracts are of great interest to numerous studies in neuroscience and medicine, their manual dissection in larger cohorts from diffusion MRI tractograms is time-consuming, requires expert knowledge and is hard to reproduce...

Artificial intelligence and breast screening: French Radiology Community position paper.

Diagnostic and interventional imaging
The objective of this article was to evaluate the evidence currently available about the clinical value of artificial intelligence (AI) in breast imaging. Nine experts from the disciplines involved in breast disease management - including physicists ...

Post-processing radio-frequency signal based on deep learning method for ultrasonic microbubble imaging.

Biomedical engineering online
BACKGROUND: Improving imaging quality is a fundamental problem in ultrasound contrast agent imaging (UCAI) research. Plane wave imaging (PWI) has been deemed as a potential method for UCAI due to its' high frame rate and low mechanical index. High fr...

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning.

Physics in medicine and biology
We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. T...

A segmentation method combining probability map and boundary based on multiple fully convolutional networks and repetitive training.

Physics in medicine and biology
Cell nuclei image segmentation technology can help researchers observe each cell's stress response to drug treatment. However, it is still a challenge to accurately segment the adherent cell nuclei. At present, image segmentation based on a fully con...

Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling.

IEEE transactions on medical imaging
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...

HYDRA: Hybrid deep magnetic resonance fingerprinting.

Medical physics
PURPOSE: Magnetic resonance fingerprinting (MRF) methods typically rely on dictionary matching to map the temporal MRF signals to quantitative tissue parameters. Such approaches suffer from inherent discretization errors, as well as high computationa...

Supervised classification approach of biometric measures for automatic fetal defect screening in head ultrasound images.

Journal of medical engineering & technology
This paper presents an advanced approach for foetal brain abnormalities diagnostic by integrating significant biometric features in the identification process. In foetal anomaly diagnosis, manual evaluation of foetal behaviour in ultrasound images is...

Enhancement of Acoustic Microscopy Lateral Resolution: A Comparison Between Deep Learning and Two Deconvolution Methods.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Scanning acoustic microscopy (SAM) provides high-resolution images of biological tissues. Since higher transducer frequencies limit penetration depth, image resolution enhancement techniques could help in maintaining sufficient lateral resolution wit...