Publications (17)
Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment
Paraskevas Pegios, Manxi Lin, Nina Weng +6
Obstetric ultrasound image quality is crucial for accurate diagnosis and monitoring of fetal health. However, acquiring high-quality standard planes is difficult, influenced by the…
From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows
Cenwei Zhang, Lin Zhu, Manxi Lin +1
Feature attributions often hide a critical modeling choice: they explain a prediction along a counterfactual path from a reference state to an input. Different baselines, interpola…
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…
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…
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…
Shortcut Learning in Medical Image Segmentation
Manxi Lin, Nina Weng, Kamil Mikolaj +5
Shortcut learning is a phenomenon where machine learning models prioritize learning simple, potentially misleading cues from data that do not generalize well beyond the training se…