6 papers
Using Explainability as a Training-Time Reliability Signal for Efficient ECG Classification
Veerendhra Kumar Dangeti, Xiao Gu, Ying Weng +1
Training deep neural networks for clinical time-series analysis is computationally demanding, yet many healthcare settings lack the resources required for repeated model developmen…
Patch-Level Glioblastoma Subregion Classification with a Contrastive Learning-Based Encoder
Juexin Zhang, Qifeng Zhong, Ying Weng +1
The significant molecular and pathological heterogeneity of glioblastoma, an aggressive brain tumor, complicates diagnosis and patient stratification. While traditional histopathol…
Robust 3D Brain MRI Inpainting with Random Masking Augmentation
Juexin Zhang, Ying Weng, Ke Chen
The ASNR-MICCAI BraTS-Inpainting Challenge was established to mitigate dataset biases that limit deep learning models in the quantitative analysis of brain tumor MRI. This paper de…
Distribution-Based Masked Medical Vision-Language Model Using Structured Reports
Shreyank N Gowda, Ruichi Zhang, Xiao Gu +2
Medical image-language pre-training aims to align medical images with clinically relevant text to improve model performance on various downstream tasks. However, existing models of…
Deep Learning for Glioblastoma Morpho-pathological Features Identification: A BraTS-Pathology Challenge Solution
Juexin Zhang, Ying Weng, Ke Chen
Glioblastoma, a highly aggressive brain tumor with diverse molecular and pathological features, poses a diagnostic challenge due to its heterogeneity. Accurate diagnosis and assess…
U-Net Based Healthy 3D Brain Tissue Inpainting
Juexin Zhang, Ying Weng, Ke Chen
This paper introduces a novel approach to synthesize healthy 3D brain tissue from masked input images, specifically focusing on the task of 'ASNR-MICCAI BraTS Local Synthesis of Ti…