AIMC Topic: Image Processing, Computer-Assisted

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Robust Blood Cell Image Segmentation Method Based on Neural Ordinary Differential Equations.

Computational and mathematical methods in medicine
For the analysis of medical images, one of the most basic methods is to diagnose diseases by examining blood smears through a microscope to check the morphology, number, and ratio of red blood cells and white blood cells. Therefore, accurate segmenta...

Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Brain ageing is a complex neurobiological process associated with morphological changes that can be assessed on MRI scans. Recently, Deep learning (DL)-based approaches have been proposed for the prediction of chronological brain age from MR images y...

Spatially-Aware Context Neural Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
A variety of computer vision tasks benefit significantly from increasingly powerful deep convolutional neural networks. However, the inherently local property of convolution operations prevents most existing models from capturing long-range feature i...

Artificial Intelligence-Based Data Corrections for Attenuation and Scatter in Position Emission Tomography and Single-Photon Emission Computed Tomography.

PET clinics
Recent developments in artificial intelligence (AI) technology have enabled new developments that can improve attenuation and scatter correction in PET and single-photon emission computed tomography (SPECT). These technologies will enable the use of ...

Precise laminae segmentation based on neural network for robot-assisted decompressive laminectomy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The decompressive laminectomy is one of the most common operations to treat lumbar spinal stenosis by removing the laminae above the spinal nerve. Recently, an increasing number of robots are deployed during the surgical pro...

Cascaded Deep Learning Neural Network for Automated Liver Steatosis Diagnosis Using Ultrasound Images.

Sensors (Basel, Switzerland)
Diagnosing liver steatosis is an essential precaution for detecting hepatocirrhosis and liver cancer in the early stages. However, automatic diagnosis of liver steatosis from ultrasound (US) images remains challenging due to poor visual quality from ...

Automatic detection of vessel structure by deep learning using intravascular ultrasound images of the coronary arteries.

PloS one
Intravascular ultrasound (IVUS) is a diagnostic modality used during percutaneous coronary intervention. However, specialist skills are required to interpret IVUS images. To address this issue, we developed a new artificial intelligence (AI) program ...

Residual dense network for medical magnetic resonance images super-resolution.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: High-resolution magnetic resonance images (MRI) help experts to localize lesions and diagnose diseases, but it is difficult to obtain high-resolution MRI. Furthermore, image super-resolution technology based on deep learning...

Deep learning for colon cancer histopathological images analysis.

Computers in biology and medicine
Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours. Unfortunately, existing methods remain limited when faced with the high resolution and size of Whole Slide Images (WSIs) coupled with the lack of richly annotat...