99 citations · 157 across the 46 of their papers we have counts for
5 papers · 1 filter
NNV3: Expanding Neural Network Verification to New Architectures and Domains
Anne M. Tumlin, Samuel Sasaki, Ben Wooding +8
We present NNV3, the latest version of the Neural Network Verification (NNV) tool, a MATLAB framework for formal verification of deep learning models and learning-enabled cyber-phy…
LISynSeg: Data-Centric Label-to-Image Synthesis for Cross-Modality Whole-Heart Segmentation
Jiacheng Wang, Ivana Isgum, Ipek Oguz
Whole-heart segmentation (WHS) in computed tomography (CT) and magnetic resonance imaging (MRI) is affected by acquisition shifts and heterogeneous cardiac annotations. Existing WH…
Towards Verified and Targeted Explanations through Formal Methods
Hanchen David Wang, Diego Manzanas Lopez, Preston K. Robinette +3
As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that are interpretable but also tru…
VAMOS-OCTA: Vessel-Aware Multi-Axis Orthogonal Supervision for Inpainting Motion-Corrupted OCT Angiography Volumes
Nick DiSanto, Ehsan Khodapanah Aghdam, Han Liu +4
Handheld Optical Coherence Tomography Angiography (OCTA) enables noninvasive retinal imaging in uncooperative or pediatric subjects, but is highly susceptible to motion artifacts t…
IntraStyler: Intra-Domain Style Synthesis for Cross-Modality MRI Domain Adaptation
Han Liu, Yubo Fan, Hao Li +5
Segmentation of vestibular schwannoma and cochlea from T2 MRI is clinically important yet annotation-intensive. Domain adaptation (DA) has been widely adopted to bridge the gap bet…