Zhang, Shaoting

StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks

Zhang, H., Xu, T., Li, H., Zhang, S., Wang, X., Huang, X., & Metaxas, D. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 3,021

A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images

Wang, G., Liu, X., Li, C., Xu, Z., Ruan, J., Zhu, H., Meng, T., Li, K., Huang, N., & Zhang, S. (2020) · IEEE Transactions on Medical Imaging

COVID-19 diagnosis using AIMedical Image Segmentation Techniques

Cited by 469

Towards robust and effective shape modeling: Sparse shape composition

Zhang, S., Zhan, Y., Dewan, M., Huang, J., Metaxas, D. N., & Zhou, X. S. (2012) · Medical Image Analysis

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 249

Multimodal Deep Learning for Cervical Dysplasia Diagnosis

Xu, T., Zhang, H., Huang, X., Zhang, S., & Metaxas, D. N. (2016) · Lecture Notes in Computer Science

AI in cancer detectionCervical Cancer and HPV Research

Cited by 187

MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning

Luo, X., Wang, G., Song, T., Zhang, J., Aertsen, M., Deprest, J., Ourselin, S., Vercauteren, T., & Zhang, S. (2021) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 126

SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Wang, H., Guo, S., Ye, J., Deng, Z., Cheng, J., Li, T., Chen, J., Su, Y., Huang, Z., Shen, Y., et al. (2023) · arXiv

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 115

High-throughput histopathological image analysis via robust cell segmentation and hashing

Zhang, X., Xing, F., Su, H., Yang, L., & Zhang, S. (2015) · Medical Image Analysis

AI in cancer detectionCell Image Analysis Techniques

Cited by 87

TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology

Wang, F.-A., Zhuang, Z., Gao, F., He, R., Zhang, S., Wang, L., Liu, J., & Li, Y. (2024) · Genome Biology

Bioinformatics and Genomic NetworksCancer Genomics and Diagnostics

Cited by 51

Evaluating and Enhancing Large Language Models’ Performance in Domain-Specific Medicine: Development and Usability Study With DocOA

Chen, X., Wang, L., You, M., Liu, W., Fu, Y., Xu, J., Zhang, S., Chen, G., Li, K., & Li, J. (2024) · Journal of Medical Internet Research

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 48

MedBench: A Comprehensive, Standardized, and Reliable Benchmarking System for Evaluating Chinese Medical Large Language Models

Liu, M., Hu, W., Ding, J., Xu, J., Li, X., Zhu, L., Bai, Z., Shi, X., Wang, B., Song, H., et al. (2024) · Big Data Mining and Analytics

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 41

Joint Kernel-Based Supervised Hashing for Scalable Histopathological Image Analysis

Jiang, M., Zhang, S., Huang, J., Yang, L., & Metaxas, D. N. (2015) · Lecture Notes in Computer Science

Image Retrieval and Classification TechniquesAI in cancer detection

Cited by 27

SAM-Med2D

Cheng, J., Ye, J., Deng, Z., Chen, J., Li, T., Wang, H., Su, Y., Huang, Z., Chen, J., Jiang, L., et al. (2023) · arXiv

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 26