Feb. 7, 2024, 5:47 a.m. | Fudan Zheng Mengfei Li Ying Wang Weijiang Yu Ruixuan Wang Zhiguang Chen Nong Xiao Yutong Lu

cs.CV updates on arXiv.org arxiv.org

Automatic radiology report generation is booming due to its huge application potential for the healthcare industry. However, existing computer vision and natural language processing approaches to tackle this problem are limited in two aspects. First, when extracting image features, most of them neglect multi-view reasoning in vision and model single-view structure of medical images, such as space-view or channel-view. However, clinicians rely on multi-view imaging information for comprehensive judgment in daily clinical diagnosis. Second, when generating reports, they overlook context …

and natural language processing application computer computer vision cs.cv features healthcare healthcare industry image industry language language processing medical natural natural language natural language processing network processing radiology reasoning report them view vision

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Engineer - AWS

@ 3Pillar Global | Costa Rica

Cost Controller/ Data Analyst - India

@ John Cockerill | Mumbai, India, India, India