6 papers
Rotation Equivariant Convolutions in Deformable Registration of Brain MRI
Arghavan Rezvani, Kun Han, Anthony T. Wu +2
Image registration is a fundamental task that aligns anatomical structures between images. While CNNs perform well, they lack rotation equivariance - a rotated input does not produ…
Benchmarking Deep Learning for Future Liver Remnant Segmentation in Colorectal Liver Metastasis
Anthony T. Wu, Arghavan Rezvani, Kela Liu +4
Accurate segmentation of the future liver remnant (FLR) is critical for surgical planning in colorectal liver metastases (CRLM) to prevent fatal post-hepatectomy liver failure. How…
MoME: Mixture of Visual Language Medical Experts for Medical Imaging Segmentation
Arghavan Rezvani, Xiangyi Yan, Anthony T. Wu +3
In this study, we propose MoME, a Mixture of Visual Language Medical Experts, for Medical Image Segmentation. MoME adapts the successful Mixture of Experts (MoE) paradigm, widely u…
XOCT: Enhancing OCT to OCTA Translation via Cross-Dimensional Supervised Multi-Scale Feature Learning
Pooya Khosravi, Kun Han, Anthony T. Wu +3
Optical Coherence Tomography Angiography (OCTA) and its derived en-face projections provide high-resolution visualization of the retinal and choroidal vasculature, which is critica…
Hyperdimensional Intelligent Sensing for Efficient Real-Time Audio Processing on Extreme Edge
Sanggeon Yun, Ryozo Masukawa, Hanning Chen +6
The escalating challenges of managing vast sensor-generated data, particularly in audio applications, necessitate innovative solutions. Current systems face significant computation…
HyperSense: Hyperdimensional Intelligent Sensing for Energy-Efficient Sparse Data Processing
Sanggeon Yun, Hanning Chen, Ryozo Masukawa +6
Introducing HyperSense, our co-designed hardware and software system efficiently controls Analog-to-Digital Converter (ADC) modules' data generation rate based on object presence p…