AIMC Topic: Image Processing, Computer-Assisted

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Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm.

Computational intelligence and neuroscience
Fuzzy clustering algorithms have received widespread attention in various fields. Point tracking technology has significant application importance in sports image data analysis. In order to solve the problem of limited tracking performance caused by ...

Image Quality Evaluation in Dual-Energy CT of the Chest, Abdomen, and Pelvis in Obese Patients With Deep Learning Image Reconstruction.

Journal of computer assisted tomography
OBJECTIVE: The aim of this study was to evaluate image quality in vascular and oncologic dual-energy computed tomography (CT) imaging studies performed with a deep learning (DL)-based image reconstruction algorithm in patients with body mass index of...

Residual RAKI: A hybrid linear and non-linear approach for scan-specific k-space deep learning.

NeuroImage
Parallel imaging is the most clinically used acceleration technique for magnetic resonance imaging (MRI) in part due to its easy inclusion into routine acquisitions. In k-space based parallel imaging reconstruction, sub-sampled k-space data are inter...

From CNNs to GANs for cross-modality medical image estimation.

Computers in biology and medicine
Cross-modality image estimation involves the generation of images of one medical imaging modality from that of another modality. Convolutional neural networks (CNNs) have been shown to be useful in image-to-image intensity projections, in addition to...

Investigating Shift Variance of Convolutional Neural Networks in Ultrasound Image Segmentation.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
While accuracy is an evident criterion for ultrasound image segmentation, output consistency across different tests is equally crucial for tracking changes in regions of interest in applications such as monitoring the patients' response to treatment,...

Deep-Learning Based Adaptive Ultrasound Imaging From Sub-Nyquist Channel Data.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Traditional beamforming of medical ultrasound images relies on sampling rates significantly higher than the actual Nyquist rate of the received signals. This results in large amounts of data to store and process, imposing hardware and software challe...

A Performance Improvement Strategy for Concrete Damage Detection Using Stacking Ensemble Learning of Multiple Semantic Segmentation Networks.

Sensors (Basel, Switzerland)
Semantic segmentation network-based methods can detect concrete damage at the pixel level. However, the performance of a single semantic segmentation network is often limited. To improve the concrete damage detection performance of a semantic segment...

Improved 3D tumour definition and quantification of uptake in simulated lung tumours using deep learning.

Physics in medicine and biology
In clinical positron emission tomography (PET) imaging, quantification of radiotracer uptake in tumours is often performed using semi-quantitative measurements such as the standardised uptake value (SUV). For small objects, the accuracy of SUV estima...

Evaluation Algorithm for the Effectiveness of Stroke Rehabilitation Treatment Using Cross-Modal Deep Learning.

Computational and mathematical methods in medicine
It is important to study the evaluation algorithm for the stroke rehabilitation treatment effect to make accurate evaluation and optimize the stroke disease treatment plan according to the evaluation results. To address the problems of poor restorati...

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

Computational intelligence and neuroscience
White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune system. They are also known as "defender cells." But the imbalance in the number of WBCs in the blood can be hazardous. Leukemia is the most common bl...