6 citations · 12 across the 7 of their papers we have counts for
7 papers
OncoReg: Medical Image Registration for Oncological Challenges
Wiebke Heyer, Yannic Elser, Lennart Berkel +16
In modern cancer research, the vast volume of medical data generated is often underutilised due to challenges related to patient privacy. The OncoReg Challenge addresses this issue…
Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Data
Yu-Cheng Chou, Bowen Li, Deng-Ping Fan +2
Creating large-scale and well-annotated datasets to train AI algorithms is crucial for automated tumor detection and localization. However, with limited resources, it is challengin…
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
Bowen Li, Yu-Cheng Chou, Shuwen Sun +3
Early detection and localization of pancreatic cancer can increase the 5-year survival rate for patients from 8.5% to 20%. Artificial intelligence (AI) can potentially assist radio…
Accurate and Generalizable Quantitative Scoring of Liver Steatosis from Ultrasound Images via Scalable Deep Learning
Bowen Li, Dar-In Tai, Ke Yan +7
Background & Aims: Hepatic steatosis is a major cause of chronic liver disease. 2D ultrasound is the most widely used non-invasive tool for screening and monitoring, but associated…
Label-Assemble: Leveraging Multiple Datasets with Partial Labels
Mintong Kang, Bowen Li, Zengle Zhu +4
The success of deep learning relies heavily on large labeled datasets, but we often only have access to several small datasets associated with partial labels. To address this probl…
Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
Bowen Li, Xinping Ren, Ke Yan +6
Depending on the application, radiological diagnoses can be associated with high inter- and intra-rater variabilities. Most computer-aided diagnosis (CAD) solutions treat such data…
Reliable Liver Fibrosis Assessment from Ultrasound using Global Hetero-Image Fusion and View-Specific Parameterization
Bowen Li, Ke Yan, Dar-In Tai +4
Ultrasound (US) is a critical modality for diagnosing liver fibrosis. Unfortunately, assessment is very subjective, motivating automated approaches. We introduce a principled deep…