AIMC Topic: Image Processing, Computer-Assisted

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Automatic generation of artificial images of leukocytes and leukemic cells using generative adversarial networks (syntheticcellgan).

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Visual analysis of cell morphology has an important role in the diagnosis of hematological diseases. Morphological cell recognition is a challenge that requires experience and in-depth review by clinical pathologists. Withi...

Computed Tomography slice interpolation in the longitudinal direction based on deep learning techniques: To reduce slice thickness or slice increment without dose increase.

PloS one
Large slice thickness or slice increment causes information insufficiency of Computed Tomography (CT) data in the longitudinal direction, which degrades the quality of CT-based diagnosis. Traditional approaches such as high-resolution computed tomogr...

Deep Learning for Image Analysis in Kidney Care.

Advances in kidney disease and health
Analysis of medical images, such as radiological or tissue specimens, is an indispensable part of medical diagnostics. Conventionally done manually, the process may sometimes be time-consuming and prone to interobserver variability. Image classificat...

Transformer-based multilevel region and edge aggregation network for magnetic resonance image segmentation.

Computers in biology and medicine
To improve the quality of magnetic resonance (MR) image edge segmentation, some researchers applied additional edge labels to train the network to extract edge information and aggregate it with region information. They have made significant progress....

Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network.

Sensors (Basel, Switzerland)
The prevalent convolutional neural network (CNN)-based image denoising methods extract features of images to restore the clean ground truth, achieving high denoising accuracy. However, these methods may ignore the underlying distribution of clean ima...

Iterative Reconstruction: State-of-the-Art and Future Perspectives.

Journal of computer assisted tomography
Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented vari...

Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal intensities that can alter the classification of not only neighboring but also distant brain tissue. The...

Fast Near-Field Frequency-Diverse Computational Imaging Based on End-to-End Deep-Learning Network.

Sensors (Basel, Switzerland)
The ability to sculpt complex reference waves and probe diverse radiation field patterns have facilitated the rise of metasurface antennas, while there is still a compromise between the required wide operation band and the non-overlapping characteris...