Latest AI and machine learning research in ophthalmology for healthcare professionals.
Recent Multimodal Large Language Models (MLLMs) have typically focused on integrating visual and textual modalities, with less emphasis placed on the role of speech in enhancing interaction. However, speech plays a crucial role in multimodal dialogue systems, and implementing high-performance in both vision and speech tasks remains a significant challenge due to the fundamental modality differen...
Image captioning is a critical task at the intersection of computer vision and natural language processing, with wide-ranging applications across various domains. For complex tasks such as diagnostic report generation, deep learning models require not only domain-specific image-caption datasets but also the incorporation of relevant general knowledge to provide contextual accuracy. Existing appr...
In recent years, 2D Vision-Language Models (VLMs) have made significant strides in image-text understanding tasks. However, their performance in 3D ...
Latent diffusion models with Transformer architectures excel at generating high-fidelity images. However, recent studies reveal an optimization dile...
Existing Medical Large Vision-Language Models (Med-LVLMs), which encapsulate extensive medical knowledge, demonstrate excellent capabilities in unde...
The design and performance analysis of relay lenses that provide high-performance image transmission for target acquisition and tracking in military...
Cybersickness remains a significant barrier to the widespread adoption of immersive virtual reality (VR) experiences, as it can greatly disrupt user...
While generative models such as text-to-image, large language models and text-to-video have seen significant progress, the extension to text-to-virt...
Thanks to the recent achievements in task-driven image quality enhancement (IQE) models like ESTR, the image enhancement model and the visual recogn...
PURPOSE: To quantify outer retina structural changes and define novel biomarkers of inherited retinal degeneration associated with biallelic mutations...
PURPOSE: To evaluate the refractive differences among school-aged children with macular or peripapillary fundus tessellation (FT) distribution pattern...
The introduction of optical coherence tomography (OCT) in the 1990s revolutionized diagnostic ophthalmic imaging. Initially, OCT's role was primarily ...
PURPOSE: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant ...
PURPOSE: Descemet membrane endothelial keratoplasty (DMEK) has emerged as a novel approach in corneal transplantation over the past two decades. This ...
Single-sequence protein structure prediction has drawn increasing attention due to the high computational costs associated with obtaining homologous i...
Diversity exists throughout biology, playing an important role in maintaining robustness and stability. The same is true of the brain, as has become i...
In pathology, reconstructing adjacent tissue parts enables an overview of the macro environment of objects like tumors. Especially, malignoma are of i...
Virtual staining is the current state-of-the-art computational technique to cleverly enhance intracellular specificity in unstained biological samples...
Despite improved outcomes with atezolizumab plus bevacizumab (A+B) in hepatocellular carcinoma (HCC), primary refractoriness (PRef), characterised by ...
Human memory is typically studied by direct questioning, and the recollection of events is investigated through verbal reports. Thus, current research...