Medical Image Enhancement
7 papers with code • 3 benchmarks • 3 datasets
Aims to improve the perceptual quality of low-quality medical images
Benchmarks
These leaderboards are used to track progress in Medical Image Enhancement
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LoDoPaB-CT
Brain Tumor MRI Dataset
Human Protein Atlas
Most implemented papers
Structure-consistent Restoration Network for Cataract Fundus Image Enhancement
liamheng/arcnet-medical-image-enhancement
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In this paper, to circumvent the strict deployment requirement, a structure-consistent restoration network (SCR-Net) for cataract fundus images is developed from synthesized data that shares an identical structure.
Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis
Au3C2/Generator-Versus-Segmentor
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Comprehensive experiments on the T2 modality of BraTS demonstrate that the proposed method substantially outperforms the state-of-the-art methods.
Deep Perceptual Enhancement for Medical Image Analysis
sharif-apu/DPE_JBHI
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IEEE Journal of Biomedical and Health Informatics 2022
Additionally, the proposed method can drastically improve the medical image analysis tasks’ performance and reveal the potentiality of such an enhancement method in real-world applications.
Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models
Diffusion models have become a popular approach for image generation and reconstruction due to their numerous advantages.
A Practical Framework for Unsupervised Structure Preservation Medical Image Enhancement
aillisinc/uspmie
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In this study, we propose a framework for practical unsupervised medical image enhancement that includes (1) a non-reference objective evaluation of structure preservation for medical image enhancement tasks called Laplacian structural similarity index measure (LaSSIM), which is based on SSIM and the Laplacian pyramid, and (2) a novel unsupervised GAN-based method called Laplacian medical image enhancement (LaMEGAN) to support the improvement of both originality and quality from LQ images.
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement
liamheng/annotation-free-medical-image-enhancement
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Additionally, a pseudo-label picker is developed to boost the knowledge distillation of enhancement tasks.
Ultrasound Image Enhancement using CycleGAN and Perceptual Loss
ShreeramAthreya/CDX-USChallenge
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These images are compared with paired images acquired from high resolution devices to demonstrate the model's ability to generate realistic high-quality images across organ systems.
