AIMC Topic: Image Processing, Computer-Assisted

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Fourier Convolution Block with global receptive field for MRI reconstruction.

Medical image analysis
Reconstructing images from under-sampled Magnetic Resonance Imaging (MRI) signals significantly reduces scan time and improves clinical practice. However, Convolutional Neural Network (CNN)-based methods, while demonstrating great performance in MRI ...

A physics-informed deep learning framework for dynamic susceptibility contrast perfusion MRI.

Medical physics
BACKGROUND: Perfusion magnetic resonance imaging (MRI)s plays a central role in the diagnosis and monitoring of neurovascular or neurooncological disease. However, conventional processing techniques are limited in their ability to capture relevant ch...

Visual Feature-Guided Diamond Convolutional Network for Finger Vein Recognition.

Sensors (Basel, Switzerland)
Finger vein (FV) biometrics have garnered considerable attention due to their inherent non-contact nature and high security, exhibiting tremendous potential in identity authentication and beyond. Nevertheless, challenges pertaining to the scarcity of...

Semi-supervised recognition for artificial intelligence assisted pathology image diagnosis.

Scientific reports
The analysis and interpretation of cytopathological images are crucial in modern medical diagnostics. However, manually locating and identifying relevant cells from the vast amount of image data can be a daunting task. This challenge is particularly ...

Creating realistic anterior segment optical coherence tomography images using generative adversarial networks.

The British journal of ophthalmology
AIMS: To develop a generative adversarial network (GAN) capable of generating realistic high-resolution anterior segment optical coherence tomography (AS-OCT) images.

Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.

Journal of imaging informatics in medicine
To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-V). Three ...

Maxillofacial bone movements-aware dual graph convolution approach for postoperative facial appearance prediction.

Medical image analysis
Postoperative facial appearance prediction is vital for surgeons to make orthognathic surgical plans and communicate with patients. Conventional biomechanical prediction methods require heavy computations and time-consuming manual operations which ha...

Lazy Resampling: Fast and information preserving preprocessing for deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Preprocessing of data is a vital step for almost all deep learning workflows. In computer vision, manipulation of data intensity and spatial properties can improve network stability and can provide an important source of gen...