output
20182025
most citedSemantic Segmentation Using Deep Learning to Extract Total Extraocular Muscles and Optic Nerve from Orbital Computed Tomography Images

45 citations

5 papers

cs.AI2025★ 36 cited

From Screens to Scenes: A Survey of Embodied AI in Healthcare

Yihao Liu, Xu Cao, Tingting Chen +7

Healthcare systems worldwide face persistent challenges in efficiency, accessibility, and personalization. Powered by modern AI technologies such as multimodal large language model…

physics.med-ph2020★ 45 cited

Semantic Segmentation Using Deep Learning to Extract Total Extraocular Muscles and Optic Nerve from Orbital Computed Tomography Images

Fubao Zhu, Zhengyuan Gao, Chen Zhao +7

Objectives: Precise segmentation of total extraocular muscles (EOM) and optic nerve (ON) is essential to assess anatomical development and progression of thyroid-associated ophthal…

eess.IV2020★ 28 cited

Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification from CT Images

Shaoping Hu, Yuan Gao, Zhangming Niu +9

An outbreak of a novel coronavirus disease (i.e., COVID-19) has been recorded in Wuhan, China since late December 2019, which subsequently became pandemic around the world. Althoug…

cs.CV2018★ 26 cited

Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study

Zhang Li, Zheyu Hu, Jiaolong Xu +10

Aim: Early detection and correct diagnosis of lung cancer are the most important steps in improving patient outcome. This study aims to assess which deep learning models perform be…

cs.CV2018★ 10 cited

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning

Tao Tan, Zhang Li, Haixia Liu +15

Bronchoscopy inspection as a follow-up procedure from the radiological imaging plays a key role in lung disease diagnosis and determining treatment plans for the patients. Doctors…