Peer-reviewed Conference Proceeding Publications

1. Dual-stream Context-aware Neural Network for Survival Prediction from Whole Slide Images
   Junxiu Gao, Shan Jin, Ranran Wang, Mingkang Wang, Tong Wang and Hongming Xu*
   Accepted in the Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. xx, 2023 (CCF-C, Acceptance rate: 37.95%)
   
2. Self-supervised contrastive pre-training integrated with multi-level co-attention for survival prognosis from whole slide images
   Junxiu Gao, Xinyu Hao, Shan Jin and Hongming Xu*
   Accepted in the 3rd International Conference on Image, Vision and Intelligent Systems, pp. xx, 2023
   
3. Predicting pathological complete response based on weakly and semi-supervised joint learning from breast cancer MRI
   Xinyu Hao, Hongming Xu*, Zhao Nannan, Yu Tao, Hamalainen Timo, and Fengyu Cong
   Accepted in Proceedings of 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. xx, 2023
   
4. SRSA-Net: Separable ResUnit and Self-Attention optimized network for simultaneous nuclei segmentation and classification in histology images
   Ranran Wang, Yusong Qiu, Yong Zhang and Hongming Xu*
   Accepted in 2023 China Biomedical Engineering Conference & Medical Innovation Summit, pp. xx-xx, 2023
   
5. Multiple instance learning for lymph node metastasis prediction from cervical cancer MRI
   Shan Jin, Hongming Xu*, Yue Dong, Xinyu Hao, Fengying Qin, Ranran Wang and Fengyu Cong
   Accepted in 20th IEEE International Symposium on Biomedical Imaging (ISBI), pp. xx-xx, 2023
   
6. Statistical Local Binary Patterns (SLBP): application to prostate cancer Gleason score prediction from whole slide pathology images
   Hongming Xu and Tae Hyun Hwang
   In 16th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 895-899, 2019
   
7. Automated detection of cavernous malformations in Brain MRI images
   Huiquan Wang, S. Nizam Ahmed, Hongming Xu and Mrinal Mandal
   In 8th International IEEE EMBS Conference on Neural Engineering,pp.17-20, 2017
   
8. Computerized measurement of melanoma depth of invasion in skin biopsy images
   Hongming Xu, Huiquan Wang, Richard Berendt, Naresh Jha and Mrinal Mandal
   In 2017 International Conference on Biomedical and Health Informatics (BHI), pp. 17-20, 2017
   Acceptance Rate: 38%
9. Automated nuclear segmentation in skin histopathological images using multi-scale radial line scanning
   Hongming Xu, Huiquan Wang, Richard Berendt, Naresh Jha and Mrinal Mandal
   In IEEE-NIH Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies, pp. 175-178, 2016
   
10. Computer aided detection of cavernous malformation in T2-weighted brain MR images
    Huiquan Wang, Hongming Xu, S.Nizam Ahmed and Mrinal Mandal,
    In IEEE-NIH Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies, pp. 101–104, 2016
    
11. Eficient segmentation of skin epidermis in whole slide histopathological images
    Hongming Xu and Mrinal Mandal
    In Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3869-3872, 2015
    
12. Automated segmentation of regions of interest in whole slide skin histopathological images
    Hongming Xu, Cheng Lu and Mrinal Mandal
    In Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3855-3858, 2015
    

Peer-reviewed Workshop Publications

1. Spatial analysis of tumor infiltrating lymphocytes based on deep learning using histopathology image to predict progression-free survival in colorectal cancer
   Hongming Xu, Yoon Jin Cha, Jean R. Clemenceau, Jinhwan Choi, Sung Hak Lee, Jeonghyun Kang, and Tae Hyun Hwang Tae Hyun Hwang
   American Association for Cancer Research Annual Meeting (AACR), April 2022
   The abstract is selected as the Oral Presentation in the meeting!
2. Transfer learning for tumor mutation burden prediction and spatial heterogeneity analysis from histopathology slides in bladder cancer
   Hongming Xu, Sung Hak Lee and Tae Hyun Hwang
   American Association for Cancer Research Annual Meeting (AACR), June 2020
3. Deep learning can predict microsatellite instability from histology in colorectal cancer across different ethnic groups
   Isaiah S. Pressman, Hongming Xu, Jeonghyun Kang, Yoon Jin Cha, Sung Hak Lee and Tae Hyun Hwang
   American Association for Cancer Research Annual Meeting (AACR), June 2020
4. Deep Gaussian processes for weakly supervised learning: tumor mutation burden (TMB) prediction
   Sunho Park, Saehoon Kim, Hongming Xu and Tae Hyun Hwang
   Bayesian Deep Learning NeurIPS 2019 Workshop, Dec 2019
5. Automatic classification of prostate cancer Gleason scores from digitized whole slide tissue biopsies
   Hongming Xu, Sunho Park and Tae Hyun Hwang
   In 17th International Workshop on Data Mining in Bioinformatics (BioKDD), August, 2018
   The top-3 oral presentations in BioKDD and poster award, and poster presentation in KDD 2018
6. Using transfer learning on whole slide images to predict tumor mutational burden in bladder cancer patients
   Hongming Xu, Sunho Park, Sung Hak Lee and Tae Hyun Hwang
   In 5th Digital Pathology AI Congress: USA, June 2019
7. Machine learning for classification of prostate cancer Gleason scores from digitized whole slide tissue biopsies
   Hongming Xu and Tae Hyun Hwang
   In 38th Annual Cleveland Clinic Research Day, Sep 2018
8. Novel lymph node segmentation for skin cancer biopsy images
   Salah Alheejawi, Hongming Xu, Richard Berendt, Naresh Jha and Mrinal Mandal
   In Proceedings of BHI-2018 International Conference on Biomedical and Health Informatics (BHI), Mar 2018
9. Automated diagnosis of melanoma from skin biopsy images
   Hongming Xu, Richard Berendt, Naresh Jha and Mrinal Mandal
   In Proceedings of BHI-2017 International Conference on Biomedical and Health Informatics (BHI), Feb 2017
10. Robust segmentation of regions of interest in skin histopathological images
    Hongming Xu and Mrinal Mandal,
    The 6th Annual Graduate Research Symposium, University of Alberta, June 2015
    Oral Presentation
11. A novel technique for nuclei segmentation in skin histopathological images
    Hongming Xu and Mrinal Mandal,
    The 5th Annual Graduate Research Symposium, University of Alberta, June 2014