AI Medical Compendium Topic

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Image Enhancement

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A deep learning-based framework for retinal fundus image enhancement.

PloS one
PROBLEM: Low-quality fundus images with complex degredation can cause costly re-examinations of patients or inaccurate clinical diagnosis.

Dental image enhancement network for early diagnosis of oral dental disease.

Scientific reports
Intelligent robotics and expert system applications in dentistry suffer from identification and detection problems due to the non-uniform brightness and low contrast in the captured images. Moreover, during the diagnostic process, exposure of sensiti...

Cerebrovascular super-resolution 4D Flow MRI - Sequential combination of resolution enhancement by deep learning and physics-informed image processing to non-invasively quantify intracranial velocity, flow, and relative pressure.

Medical image analysis
The development of cerebrovascular disease is tightly coupled to regional changes in intracranial flow and relative pressure. Image-based assessment using phase contrast magnetic resonance imaging has particular promise for non-invasive full-field ma...

Deep learning-based image enhancement in optical coherence tomography by exploiting interference fringe.

Communications biology
Optical coherence tomography (OCT), an interferometric imaging technique, provides non-invasive, high-speed, high-sensitive volumetric biological imaging in vivo. However, systemic features inherent in the basic operating principle of OCT limit its i...

Dose reduction and image enhancement in micro-CT using deep learning.

Medical physics
BACKGROUND: In preclinical settings, micro-computed tomography (CT) provides a powerful tool to acquire high resolution anatomical images of rodents and offers the advantage to in vivo non-invasively assess disease progression and therapy efficacy. M...

Four-Dimensional Cone Beam CT Imaging Using a Single Routine Scan via Deep Learning.

IEEE transactions on medical imaging
A novel method is proposed to obtain four-dimensional (4D) cone-beam computed tomography (CBCT) images from a routine scan in patients with upper abdominal cancer. The projections are sorted according to the location of the lung diaphragm before bein...

A Feasibility Study on Deep Learning Reconstruction to Improve Image Quality With PROPELLER Acquisition in the Setting of T2-Weighted Gynecologic Pelvic Magnetic Resonance Imaging.

Journal of computer assisted tomography
OBJECTIVES: Evaluate deep learning (DL) to improve the image quality of the PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction technique) for 3 T magnetic resonance imaging of the female pelvis.

An Underwater Image Enhancement Method for a Preprocessing Framework Based on Generative Adversarial Network.

Sensors (Basel, Switzerland)
This paper presents an efficient underwater image enhancement method, named ECO-GAN, to address the challenges of color distortion, low contrast, and motion blur in underwater robot photography. The proposed method is built upon a preprocessing frame...

Artificial intelligence-enabled quantitative phase imaging methods for life sciences.

Nature methods
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and label-free investigation of the physiology and pathology of biological systems. This review presents the principles of various two-dimensional and three-dim...

SSP-Net: A Siamese-Based Structure-Preserving Generative Adversarial Network for Unpaired Medical Image Enhancement.

IEEE/ACM transactions on computational biology and bioinformatics
Recently, unpaired medical image enhancement is one of the important topics in medical research. Although deep learning-based methods have achieved remarkable success in medical image enhancement, such methods face the challenge of low-quality traini...