output
20142024
most citedVisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence

72 citations

8 papers

cs.RO2024★ 13 cited

A Magnetic Millirobot Walks on Slippery Biological Surfaces for Targeted Cargo Delivery

Moonkwang Jeong, Xiangzhou Tan, Felix Fischer +1

Small-scale robots hold great potential for targeted cargo delivery in minimally-inv asive medicine. However, current robots often face challenges to locomote efficiently on slip p…

eess.IV2023★ 72 cited

VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence

Jianing Qiu, Jian Wu, Hao Wei +39

We present VisionFM, a foundation model pre-trained with 3.4 million ophthalmic images from 560,457 individuals, covering a broad range of ophthalmic diseases, modalities, imaging…

physics.optics2023★ 19 cited

Single-shot quantitative differential phase contrast imaging combined with programmable polarization multiplexing illumination

Siying Liu, Chuanjian Zheng, Qun Hao +2

We propose a single-shot quantitative differential phase contrast (DPC) method with polarization multiplexing illumination. In the illumination module of our system, the programmab…

eess.IV2022★ 10 cited

Automatic reorientation by deep learning to generate short axis SPECT myocardial perfusion images

Fubao Zhu, Guojie Wang, Chen Zhao +6

Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpre…

eess.IV2022

Preparing data for pathological artificial intelligence with clinical-grade performance

Yuanqing Yang, Kai Sun, Yanhua Gao +2

[Purpose] The pathology is decisive for disease diagnosis, but relies heavily on the experienced pathologists. Recently, pathological artificial intelligence (PAI) is thought to im…

cs.CL2021★ 19 cited

More but Correct: Generating Diversified and Entity-revised Medical Response

Bin Li, Encheng Chen, Hongru Liu +5

Medical Dialogue Generation (MDG) is intended to build a medical dialogue system for intelligent consultation, which can communicate with patients in real-time, thereby improving t…