245 citations · 923 across the 38 of their papers we have counts for
7 papers · 1 filter
Sharp-GAN: Sharpness Loss Regularized GAN for Histopathology Image Synthesis
Sujata Butte, Haotian Wang, Min Xian +1
Existing deep learning-based approaches for histopathology image analysis require large annotated training sets to achieve good performance; but annotating histopathology images is…
TA-Net: Topology-Aware Network for Gland Segmentation
Haotian Wang, Min Xian, Aleksandar Vakanski
Gland segmentation is a critical step to quantitatively assess the morphology of glands in histopathology image analysis. However, it is challenging to separate densely clustered g…
BI-RADS-Net: An Explainable Multitask Learning Approach for Cancer Diagnosis in Breast Ultrasound Images
Boyu Zhang, Aleksandar Vakanski, Min Xian
In healthcare, it is essential to explain the decision-making process of machine learning models to establish the trustworthiness of clinicians. This paper introduces BI-RADS-Net,…
Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images
Haotian Wang, Aleksandar Vakanski, Changfa Shi +1
Separating overlapped nuclei is a major challenge in histopathology image analysis. Recently published approaches have achieved promising overall performance on nuclei segmentation…
Understanding Fission Gas Bubble Distribution, Lanthanide Transportation, and Thermal Conductivity Degradation in Neutron-irradiated α-U Using Machine Learning
Lu Cai, Fei Xu, Fidelma Dilemma +6
UZr based metallic nuclear fuel is the leading candidate for next-generation sodium-cooled fast reactors in the United States. US research reactors have been using and testing this…
Evaluation of Complexity Measures for Deep Learning Generalization in Medical Image Analysis
Aleksandar Vakanski, Min Xian
The generalization performance of deep learning models for medical image analysis often decreases on images collected with different devices for data acquisition, device settings,…
Multi-Slice Low-Rank Tensor Decomposition Based Multi-Atlas Segmentation: Application to Automatic Pathological Liver CT Segmentation
Changfa Shi, Min Xian, Xiancheng Zhou +2
Liver segmentation from abdominal CT images is an essential step for liver cancer computer-aided diagnosis and surgical planning. However, both the accuracy and robustness of exist…