1.1k citations · 1.1k across the 5 of their papers we have counts for
6 papers
Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography
Xuxin Chen, Yuheng Li, Mingzhe Hu +5
Although fusion of information from multiple views of mammograms plays an important role to increase accuracy of breast cancer detection, developing multi-view mammograms-based com…
Developing a Novel Image Marker to Predict the Clinical Outcome of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer Patients
Ke Zhang, Neman Abdoli, Patrik Gilley +7
Objective Neoadjuvant chemotherapy (NACT) is one kind of treatment for advanced stage ovarian cancer patients. However, due to the nature of tumor heterogeneity, the clinical outco…
Evaluating the Effectiveness of 2D and 3D Features for Predicting Tumor Response to Chemotherapy
Neman Abdoli, Ke Zhang, Patrik Gilley +7
2D and 3D tumor features are widely used in a variety of medical image analysis tasks. However, for chemotherapy response prediction, the effectiveness between different kinds of 2…
Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms
Xuxin Chen, Ke Zhang, Neman Abdoli +5
Deep convolutional neural networks (CNNs) have been widely used in various medical imaging tasks. However, due to the intrinsic locality of convolution operation, CNNs generally ca…
Virtual Adversarial Training for Semi-supervised Breast Mass Classification
Xuxin Chen, Ximin Wang, Ke Zhang +7
This study aims to develop a novel computer-aided diagnosis (CAD) scheme for mammographic breast mass classification using semi-supervised learning. Although supervised deep learni…
Recent advances and clinical applications of deep learning in medical image analysis
Xuxin Chen, Ximin Wang, Ke Zhang +7
Deep learning has received extensive research interest in developing new medical image processing algorithms, and deep learning based models have been remarkably successful in a va…