RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmark

Ophthalmologists have used fundus images to screen and diagnose eye diseases. However, different equipments and ophthalmologists pose large variations to the quality of fundus images. Low-quality (LQ) degraded fundus images easily lead to uncertainty in clinical screening and generally increase the risk of misdiagnosis. Thus, real fundus image restoration is worth studying. Unfortunately, real clinical benchmark has not been explored for this task so far. In this paper, we investigate the real clinical fundus image restoration problem. Firstly, We establish a clinical dataset, Real Fundus (RF), including 120 low- and high-quality (HQ) image pairs. Then we propose a novel Transformer-based Generative Adversarial Network (RFormer) to restore the real degradation of clinical fundus images. The key component in our network is the Window-based Self-Attention Block (WSAB) which captures non-local self-similarity and long-range dependencies. To produce more visually pleasant results, a Transformer-based discriminator is introduced. Extensive experiments on our clinical benchmark show that the proposed RFormer significantly outperforms the state-of-the-art (SOTA) methods. In addition, experiments of downstream tasks such as vessel segmentation and optic disc/cup detection demonstrate that our proposed RFormer benefits clinical fundus image analysis and applications. The dataset, code, and models will be released.

Effect of surface treatment on vibration energy transfer of ultrasonic sonotrode

In this paper, two kinds of ultrasonic radiation rod with surface treatment (ion nitriding and vacuum carburizing) are selected to carry out finite element analysis on ultrasonic vibration system and casting system, and explore the influence of surface treatment on vibration energy transmission of radiation rod. The cavitation field of radiation rod with different surface treatment in water was obtained through the cavitation erosion area of aluminum foil in water by using the aluminum foil cavitation experiment, so as to verify the simulation results of sound pressure field in aluminum melt. The results show that the surface treatment weakens the vibration response of the radiating rod, reduces the longitudinal amplitude of the radiating rod, and reduces the amplitude of sound pressure transmitted into the aluminum melt.