Zobrazeno 1 - 10
of 159
pro vyhledávání: '"Shi Danli"'
Autor:
Chen, Ruoyu, Zhang, Weiyi, Liu, Bowen, Chen, Xiaolan, Xu, Pusheng, Liu, Shunming, He, Mingguang, Shi, Danli
The rising prevalence of vision-threatening retinal diseases poses a significant burden on the global healthcare systems. Deep learning (DL) offers a promising solution for automatic disease screening but demands substantial data. Collecting and labe
Externí odkaz:
http://arxiv.org/abs/2411.10004
Autor:
Chen, Xiaolan, Chen, Ruoyu, Xu, Pusheng, Zhang, Weiyi, Shang, Xianwen, He, Mingguang, Shi, Danli
Accurate diagnosis of ophthalmic diseases relies heavily on the interpretation of multimodal ophthalmic images, a process often time-consuming and expertise-dependent. Visual Question Answering (VQA) presents a potential interdisciplinary solution by
Externí odkaz:
http://arxiv.org/abs/2410.16662
Autor:
Zhang, Weiyi, Yang, Jiancheng, Chen, Ruoyu, Huang, Siyu, Xu, Pusheng, Chen, Xiaolan, Lu, Shanfu, Cao, Hongyu, He, Mingguang, Shi, Danli
Fundus fluorescein angiography (FFA) is crucial for diagnosing and monitoring retinal vascular issues but is limited by its invasive nature and restricted accessibility compared to color fundus (CF) imaging. Existing methods that convert CF images to
Externí odkaz:
http://arxiv.org/abs/2410.13242
Autor:
Shi, Danli, Zhang, Weiyi, Yang, Jiancheng, Huang, Siyu, Chen, Xiaolan, Yusufu, Mayinuer, Jin, Kai, Lin, Shan, Liu, Shunming, Zhang, Qing, He, Mingguang
Early detection of eye diseases like glaucoma, macular degeneration, and diabetic retinopathy is crucial for preventing vision loss. While artificial intelligence (AI) foundation models hold significant promise for addressing these challenges, existi
Externí odkaz:
http://arxiv.org/abs/2409.06644
Autor:
Zhang, Weiyi, Huang, Siyu, Yang, Jiancheng, Chen, Ruoyu, Ge, Zongyuan, Zheng, Yingfeng, Shi, Danli, He, Mingguang
Fundus Fluorescein Angiography (FFA) is a critical tool for assessing retinal vascular dynamics and aiding in the diagnosis of eye diseases. However, its invasive nature and less accessibility compared to Color Fundus (CF) images pose significant cha
Externí odkaz:
http://arxiv.org/abs/2408.15217
Ultrawide-field fluorescein angiography (UWF-FA) facilitates diabetic retinopathy (DR) detection by providing a clear visualization of peripheral retinal lesions. However, the intravenous dye injection with potential risks hamper its application. We
Externí odkaz:
http://arxiv.org/abs/2408.10636
Choroidal Vessel Segmentation on Indocyanine Green Angiography Images via Human-in-the-Loop Labeling
Human-in-the-loop (HITL) strategy has been recently introduced into the field of medical image processing. Indocyanine green angiography (ICGA) stands as a well-established examination for visualizing choroidal vasculature and detecting chorioretinal
Externí odkaz:
http://arxiv.org/abs/2406.01993
Publikováno v:
Pteridines, Vol 31, Iss 1, Pp 158-164 (2020)
Objective Folate deficiency is closely related to the occurrence of human tumors and plays an important role in cell growth, differentiation, repair, and host defense. We studied the effects of folic acid on the apoptosis of breast cancer cells (MDA-
Externí odkaz:
https://doaj.org/article/a475342038d04f4b99e655b47c64605a
Autor:
Shi, Danli, Zhang, Weiyi, Chen, Xiaolan, Liu, Yexin, Yang, Jiancheng, Huang, Siyu, Tham, Yih Chung, Zheng, Yingfeng, He, Mingguang
Artificial intelligence (AI) is vital in ophthalmology, tackling tasks like diagnosis, classification, and visual question answering (VQA). However, existing AI models in this domain often require extensive annotation and are task-specific, limiting
Externí odkaz:
http://arxiv.org/abs/2405.11338
Large language models (LLMs) have emerged as powerful tools with transformative potential across numerous domains, including healthcare and medicine. In the medical domain, LLMs hold promise for tasks ranging from clinical decision support to patient
Externí odkaz:
http://arxiv.org/abs/2405.07468