1 citations · 2 across the 4 of their papers we have counts for
5 papers
FD-AA: A Lightweight Focal-Diffuse And Attenuation-Aware Head for Incidental Abdominal Abnormality Detection in Chest CT
Haoyan Ding, Kritika Iyer, Halid Yerebakan +9
Routine chest CT captures upper-abdominal structures that may contain clinically relevant incidental abnormalities. Detecting these findings requires feature extraction from organs…
AGA3DNet: Anatomy-Guided Gaussian Priors with Multi-view xLSTM for 3D Brain MRI Subtype Classification
Peiyu Duan, Xueqi Guo, Sepehr Farhand +5
Accurate 3D brain MRI subtype classification benefits from both localized anatomical cues and long-range contextual reasoning. We present AGA3DNet, a report-grounded framework that…
DD-CISENet: Dual-Domain Cross-Iteration Squeeze and Excitation Network for Accelerated MRI Reconstruction
Xiongchao Chen, Zhigang Peng, Gerardo Hermosillo Valadez
Magnetic resonance imaging (MRI) is widely employed for diagnostic tests in neurology. However, the utility of MRI is largely limited by its long acquisition time. Acquiring fewer…
Deep Generative Neural Embeddings for High Dimensional Data Visualization
Halid Ziya Yerebakan, Gerardo Hermosillo Valadez
We propose a visualization technique that utilizes neural network embeddings and a generative network to reconstruct original data. This method allows for independent manipulation…
Dual-Domain Cross-Iteration Squeeze-Excitation Network for Sparse Reconstruction of Brain MRI
Xiongchao Chen, Yoshihisa Shinagawa, Zhigang Peng +1
Magnetic resonance imaging (MRI) is one of the most commonly applied tests in neurology and neurosurgery. However, the utility of MRI is largely limited by its long acquisition tim…