AIMC Topic: Image Processing, Computer-Assisted

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Swin-MFA: A Multi-Modal Fusion Attention Network Based on Swin-Transformer for Low-Light Image Human Segmentation.

Sensors (Basel, Switzerland)
In recent years, image segmentation based on deep learning has been widely used in medical imaging, automatic driving, monitoring and security. In the fields of monitoring and security, the specific location of a person is detected by image segmentat...

Deep learning based correction of low performing pixel in computed tomography.

Biomedical physics & engineering express
Low Performing Pixel (LPP)/bad pixel in CT detectors cause ring and streaks artifacts, structured non-uniformities and deterioration of the image quality. These artifacts make the image unusable for diagnostic purposes. A missing/defective detector p...

Tooth CT Image Segmentation Method Based on the U-Net Network and Attention Module.

Computational and mathematical methods in medicine
Traditional image segmentation methods often encounter problems of low segmentation accuracy and being time-consuming when processing complex tooth Computed Tomography (CT) images. This paper proposes an improved segmentation method for tooth CT imag...

Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN)...

Detecting and Classifying Nuclei Using Multi-Scale Fully Convolutional Network.

Journal of computational biology : a journal of computational molecular cell biology
The detection and classification of nuclei play an important role in the histopathological analysis. It aims to find out the distribution of nuclei in the histopathology images for the next step of analysis and research. However, it is very challengi...

ABSSNet: Attention-Based Spatial Segmentation Network for Traffic Scene Understanding.

IEEE transactions on cybernetics
The location information of road and lane lines is the supremely important thing for the automatic drive and auxiliary drive. The detection accuracy of these two elements dramatically affects the reliability and practicality of the whole system. In r...

Dual-Branch Discrimination Network Using Multiple Sparse Priors for Image Deblurring.

Sensors (Basel, Switzerland)
Blind image deblurring is a challenging problem in computer vision, aiming to restore the sharp image from blurred observation. Due to the incompatibility between the complex unknown degradation and the simple synthetic model, directly training a dee...

Metaheuristic Optimization-Driven Novel Deep Learning Approach for Brain Tumor Segmentation.

BioMed research international
Brain tumor has the foremost distinguished etiology of high morality. Neoplasm, a categorization of brain tumors, is very operative in distinguishing and determining the tumor's exact location in the brain. Magnetic resonance imaging (MRI) is an effi...