3 citations · 7 across the 10 of their papers we have counts for
6 papers · 1 filter
MIRAGE: Towards AI-Generated Image Detection in the Wild
Cheng Xia, Manxi Lin, Jiexiang Tan +6
The spreading of AI-generated images (AIGI), driven by advances in generative AI, poses a significant threat to information security and public trust. Existing AIGI detectors, whil…
Incorporating Clinical Guidelines through Adapting Multi-modal Large Language Model for Prostate Cancer PI-RADS Scoring
Tiantian Zhang, Manxi Lin, Hongda Guo +4
The Prostate Imaging Reporting and Data System (PI-RADS) is pivotal in the diagnosis of clinically significant prostate cancer through MRI imaging. Current deep learning-based PI-R…
Learning semantic image quality for fetal ultrasound from noisy ranking annotation
Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer +9
We introduce the notion of semantic image quality for applications where image quality relies on semantic requirements. Working in fetal ultrasound, where ranking is challenging an…
Removing confounding information from fetal ultrasound images
Kamil Mikolaj, Manxi Lin, Zahra Bashir +4
Confounding information in the form of text or markings embedded in medical images can severely affect the training of diagnostic deep learning algorithms. However, data collected…
Explainable fetal ultrasound quality assessment with progressive concept bottleneck models
Manxi Lin, Aasa Feragen, Kamil Mikolaj +3
The quality of fetal ultrasound screening scans directly influences the precision of biometric measurements. However, acquiring high-quality scans is labor-intensive and highly rel…
diffConv: Analyzing Irregular Point Clouds with an Irregular View
Manxi Lin, Aasa Feragen
Standard spatial convolutions assume input data with a regular neighborhood structure. Existing methods typically generalize convolution to the irregular point cloud domain by fixi…