1 citations · 1 across the 7 of their papers we have counts for
7 papers
An Interpretable Deep Learning Framework for Discovery and Clinical Validation of Deep Radiomic Signatures in Tumor Classification
Chengkun Sun, Jinqian Pan, Renjie Liang +7
Imaging signatures are quantitative features extracted from medical images that provide clinically meaningful information for tumor diagnosis, characterization, prognosis, and trea…
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…
Enhancing Renal Tumor Malignancy Prediction: Deep Learning with Automatic 3D CT Organ Focused Attention
Zhengkang Fan, Chengkun Sun, Russell Terry +2
Accurate prediction of malignancy in renal tumors is crucial for informing clinical decisions and optimizing treatment strategies. However, existing imaging modalities lack the nec…
A Clinically-Grounded Two-Stage Framework for Renal CT Report Generation
Renjie Liang, Zhengkang Fan, Jinqian Pan +4
Objective Renal cancer is a common malignancy and a major cause of cancer-related deaths. Computed tomography (CT) is central to early detection, staging, and treatment planning. H…
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…