5 papers
Asymmetric Paired-Annotation Learning for Multi-Structure ULF Pediatric Brain MRI Segmentation
Ha-Hieu Pham, Dang P. M. Cao, Minh Hoang Pham +4
Portable ultra-low-field (ULF) MRI can expand access to pediatric neuroimaging, but segmentation at 0.064 T remains challenging because anatomical boundaries are weakly delineated,…
When Oracle Conditioning Misleads Deployment: Conditioning-Availability Bias in Echocardiographic Segmentation
Dang P. M. Cao, Hieu D. Pham, Hieu Pham
Conditional segmentation models may be trained and evaluated with auxiliary signals cleaner than those available at deployment. We study this protocol-level manifestation of shortc…
When Measurement Conventions Masquerade as Calibration Gains in Cardiac Digital Twins
Dang P. M. Cao, Hieu Pham
Cardiac digital twins convert clinical images into physiological measurements through observation operators, yet calibration studies often assume a fixed reference convention. Acro…
Beyond Uncertainty: Generalizable Failure Monitoring for Surgical Segmentation under Acquisition Degradation
Hieu D. Pham, Dang P. M. Cao, Thanh Trung Huynh
Surgical segmentation networks can fail silently under acquisition degradation: predicted masks may be wrong even when model confidence remains high. Existing deployment-time monit…
Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification
Ha-Hieu Pham, Hai-Dang Nguyen, Dang P. M. Cao +5
In chest X-ray (CXR) classification, acceptable ranking performance can still leave rare-positive patients below threshold, especially within subgroups. We study this pre-deploymen…