Dou, Qi

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Ehteshami Bejnordi, B., Veta, M., Johannes van Diest, P., van Ginneken, B., Karssemeijer, N., Litjens, G., van der Laak, J. A. W. M., and the CAMELYON16 Consortium, Hermsen, M., Manson, Q. F., et al. (2017) · JAMA

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 3,293

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2019) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2023) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks

Yu, L., Chen, H., Dou, Q., Qin, J., & Heng, P.-A. (2017) · IEEE Transactions on Medical Imaging

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 1,140

Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks

Dou, Q., Chen, H., Yu, L., Zhao, L., Qin, J., Wang, D., Mok, V. C., Shi, L., & Heng, P.-A. (2016) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesIntracerebral and Subarachnoid Hemorrhage Research

Cited by 679

Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 394

3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes

Dou, Q., Chen, H., Jin, Y., Yu, L., Qin, J., & Heng, P.-A. (2016) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 344

SV-RCNet: Workflow Recognition From Surgical Videos Using Recurrent Convolutional Network

Jin, Y., Dou, Q., Chen, H., Yu, L., Qin, J., Fu, C.-W., & Heng, P.-A. (2018) · IEEE Transactions on Medical Imaging

Surgical Simulation and TrainingMedical Image Segmentation Techniques

Cited by 316

Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study

Dou, Q., So, T. Y., Jiang, M., Liu, Q., Vardhanabhuti, V., Kaissis, G., Li, Z., Si, W., Lee, H. H. C., Yu, K., et al. (2021) · npj Digital Medicine

COVID-19 diagnosis using AIPrivacy-Preserving Technologies in Data

Cited by 278

Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks

Chen, H., Dou, Q., Ni, D., Cheng, J.-Z., Qin, J., Li, S., & Heng, P.-A. (2015) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 180

Ultrasound Standard Plane Detection Using a Composite Neural Network Framework

Chen, H., Wu, L., Dou, Q., Qin, J., Li, S., Cheng, J.-Z., Ni, D., & Heng, P.-A. (2017) · IEEE Transactions on Cybernetics

Medical Image Segmentation TechniquesPrenatal Screening and Diagnostics

Cited by 164

3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

Gong, S., Zhong, Y., Ma, W., Li, J., Wang, Z., Zhang, J., Heng, P.-A., & Dou, Q. (2024) · Medical Image Analysis

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 156

Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects

Glocker, B., Robinson, R., Castro, D. C., Dou, Q., & Konukoglu, E. (2019) · arXiv

Advanced MRI Techniques and ApplicationsFunctional Brain Connectivity Studies

Cited by 74