1 citations · 1 across the 7 of their papers we have counts for
7 papers
Multi-Granularity 3D Kidney Lesion Characterization from CT Volumes
Renjie Liang, Zhengkang Fan, Jinqian Pan +4
Radiology reports describe kidney lesions by type, size, enhancement, and attenuation, yet existing 3D methods predict only at the patient or organ level. We reformulate kidney CT…
OphMAE: Bridging Volumetric and Planar Imaging with a Foundation Model for Adaptive Ophthalmological Diagnosis
Tienyu Chang, Zhen Chen, Renjie Liang +9
The advent of foundation models has heralded a new era in medical artificial intelligence (AI), enabling the extraction of generalizable representations from large-scale unlabeled…
SAIL: Structure-Aware Interpretable Learning for Anatomy-Aligned Post-hoc Explanations in OCT
Tienyu Chang, Tianhao Li, Ruogu Fang +2
Optical coherence tomography (OCT), a commonly used retinal imaging modality, plays a central role in retinal disease diagnosis by providing high-resolution visualization of retina…
DTC: A Deformable Transposed Convolution Module for Medical Image Segmentation
Chengkun Sun, Jinqian Pan, Renjie Liang +4
In medical image segmentation, particularly in UNet-like architectures, upsampling is primarily used to transform smaller feature maps into larger ones, enabling feature fusion bet…
GASA-UNet: Global Axial Self-Attention U-Net for 3D Medical Image Segmentation
Chengkun Sun, Russell Stevens Terry, Jiang Bian +1
Accurate segmentation of multiple organs and the differentiation of pathological tissues in medical imaging are crucial but challenging, especially for nuanced classifications and…
BGDB: Bernoulli-Gaussian Decision Block with Improved Denoising Diffusion Probabilistic Models
Chengkun Sun, Jinqian Pan, Russell Stevens Terry +2
Generative models can enhance discriminative classifiers by constructing complex feature spaces, thereby improving performance on intricate datasets. Conventional methods typically…
Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities
Chengkun Sun, Jinqian Pan, Zhuoli Jin +3
Training deep Convolutional Neural Networks (CNNs) presents unique challenges, including the pervasive issue of elimination singularities, consistent deactivation of nodes leading…