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Recent Publications:

  1. H. Wang, M. Xian, and A. Vakanski, “Bending Loss Regularized Network for Nuclei Segmentation in Histopathology Images,” in IEEE International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 2020, pp. 1-5.
  2. F. Xu, Y. Zhang, M. Xian, H.D. Cheng, B. Zhang, J. Ding, C. Ning, and Y. Wang, “Breast Anatomy Enriched Tumor Saliency Estimation,” in 25th International Conference on Pattern Recognition, 2020.
  3. A. Vakanski, M. Xian, and P. Freer, “Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images,” Ultrasound in Medicine & Biology, 2020. IF=2.51
  4. B. Shareef, M. Xian, and A. Vakanski, “STAN: Small tumor-aware network for breast ultrasound image segmentation,” in IEEE 17th International Symposium on Biomedical Imaging, 2020.
  5. B. Shareef, A. Vakanski, M. Xian, and P. E. Freer, “ESTAN: Enhanced Small Tumor-Aware Network for Breast Ultrasound Image Segmentation,” arXiv preprint arXiv:2009.12894, 2020.
  6. Y. Liao, A. Vakanski, M. Xian, D. Paul, and R. Baker, “A review of computational approaches for evaluation of rehabilitation exercises,” Computers in Biology and Medicine, vol. 119, pp. 103687, 2020/04/01/, 2020. IF=3.43
  7. Y. Liao, A. Vakanski, and M. Xian, “A Deep Learning Framework for Assessing Physical Rehabilitation Exercises,” IEEE Trans Neural Syst Rehabil Eng, vol. 28, no. 2, pp. 468-477, Feb, 2020. IF=4.11
  8. H. Guan, Y. Zhang, M. Xian, H. Cheng, and X. Tang, “SMOTE-WENN: Solving class imbalance and small sample problems by oversampling and distance scaling,” Applied Intelligence, pp. 1-16, 2020. IF=3.26
  9. B. Hersh, A. Mohajeri, A. Mirkouei, and M. Xian, “Cyber-Physical Infrastructures for Advancing Pyrolysis Conversion Process: A Case Study of Biochar Production,” in International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2020, pp. V009T09A002.
  10. M. B. Badsha, R. Li, B. Liu, Y. I. Li, M. Xian, N. E. Banovich, and A. Fu, “Imputation of single-cell gene expression with an autoencoder neural network,” Quantitative Biology, vol. 8, no. 1, pp. 78-94, 2020.
  1. H. Guan, Y. Zhang, H.D. Cheng, M. Xian, and X. Tang, “BA2Cs: Bounded abstaining with two constraints of reject rates in binary classification,” Neurocomputing, vol. 357, pp. 125-134, 2019. IF=5.19
  2. F. Xu, Y. Zhang, M. Xian, H. Cheng, B. Zhang, J. Ding, C. Ning, and Y. Wang, “Tumor Saliency Estimation for Breast Ultrasound Images via Breast Anatomy Modeling,” arXiv preprint arXiv:1906.07760, 2019.
  3. S. Hansen, A. Mirkouei, and M. Xian, “Cyber-Physical Control and Optimization for Biofuel 4.0,” in IISE Annual Conference & Expo, New Orleans, 2019.
  4. A. Acharya, Y. Hou, Y. Mao, M. Xian, and J. Yuan, “Workload-Aware Task Placement in Edge-Assisted Human Re-identification,” in 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 2019, pp. 1-9.
  1. M. Xian, Y. Zhang, H. D. Cheng, F. Xu, J. Ding, Automatic breast ultrasound image segmentation: a survey, Pattern Recognition, vol. 79, pp. 340-355, 2018. IF=7.20
  2. F. Xu, M. Xian, Y. Zhang, K. Huang, H.-D. Cheng, B. Zhang, J. Ding, C. Ning, and Y. Wang, “A Hybrid Framework for Tumor Saliency Estimation,” in International Conference on Pattern Recognition (ICPR), Beijing, China, 2018, pp. 3935-3940.
  3. B. Zhang, Y. Zhang, H. Cheng, M. Xian, S. Gai, O. Cheng, and K. Huang, Computer-Aided Knee Joint Magnetic Resonance Image Segmentation-A Survey, arXiv preprint arXiv:1802.04894, 2018.
  4. M. Xian, Y. Zhang, H. Cheng, F. Xu, K. Huang, B. Zhang, J. Ding, C. Ning, and Y. Wang, “A Benchmark for Breast Ultrasound Image Segmentation (BUSIS),” arXiv preprint arXiv:1801.03182, 2018.
  5. F. Wei, J. Ding, C. Ning, F. Xu, M. Xian, and Y. Zhang, “Texture analysis and imbalanced data processing for papillary thyroid microcarcinoma detection,” in International Conference on Biological Information and Biomedical Engineering, Shanghai, China, 2018, pp. 1-4.
  6. Y. Luo, M. Xian, M. Mohanpurkar, B. P. Bhattarai, A. Medarn, R. Kadavil, and R. Hovsapian, “Optimal Scheduling of Electrolyzer in Power Market with Dynamic Prices,” in IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Boise, ID, USA, 2018, pp. 1-6.
  7. Y. Wang, R. Ni, Y. Zhao, and M. Xian, “Watermark Embedding for Direct Binary Searched Halftone Images by Adopting Visual Cryptography,” Computers, Materials & Continua (CMC), 2018.

2011 - 2017:
  1. M. Xian, Y. Zhang, H. D. Cheng, F. Xu, J. Ding, Neutro-Connectedness Cut, IEEE Transactions on Image Processing, 25(2016) 4691-4703. [arXiv | Datasets: Grabcut, NC-Cut, Looseness28] IF=8.98
  2. H. Guan, Y. Zhang, M. Xian, H.D. Cheng, X. Tang, WENN for Individualized Cleaning in Imbalanced Data, in ICPR, 2016, pp. 456-461. 
  3. M. Xian, F. Xu, H. D. Cheng, EISeg: Effective Interactive Segmentation, in ICPR , 2016, pp. 1982-1987 [PDF, Code avaliable upon request]
  4. F. Xu, M. Xian, H. D. Cheng, Unsupervised Saliency Estimation based on Robust Hypotheses, in IEEE WACV, 2016, pp. 1-6. [PDF, Code avaliable upon request]
  5. C. Liu, H. D. Cheng, Y. Wang, Y. Zhang, M. Xian, Robust Multiple Cue Fusion Based High-Speed and Non-Rigid Object Tracking Algorithm for Short Track Speed Skating, Journal of Electronic Imaging, 25 (2016), 0130141-01301416. [Link]
  6. M. Xian, Y. Zhang, H. D. Cheng, Fully Automatic Segmentation of Breast Ultrasound Images Based on Breast Characteristics in Space and Frequency Domains, Pattern Recognition, 48(2015) 485-497. [PDF, Poster, Demo: Seed generation, Segmentation] IF=7.20
  7. J. Ding, H. D. Cheng, M. Xian, Y. Zhang, F. Xu, Local-weighted Citation-kNN algorithm for breast ultrasound image classification, Optik - International Journal for Light and Electron Optics, 126 (2015) 5188-5193. [Link] IF=2.11
  8. J. Ding, M. Xian, H. D. Cheng, An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography, in IEEE ICIP, 2015, pp. 4224-4227. [PDF]
  9. H. Shao, Y. Zhang, M. Xian, H. D. Cheng, F. Xu, J. Ding, A Saliency model for automated tumor detection in breast ultrasound images, in IEEE ICIP, 2015, pp. 1424-1428. [PDF]
  10. M. Xian, Y. Zhang, H. D. Cheng, A Fully Automatic Breast Ultrasound Image Segmentation Approach Based on Neutro-Connectedness, in ICPR, 2014, pp. 2495-2500. [PDF]
  11. H. Yu, M. Xian, X. Qi, Unsupervised Co-segmentation Based on Co-saliency Model and a New Global GMM Constraint in MRF, in IEEE ICIP, 2014, pp. 4412-4416. [PDF]
  12. M. Xian, J. Huang, Y. Zhang, X. Tang, Multiple-domain knowledge based MRF model for tumor segmentation in breast ultrasound images, in IEEE ICIP, 2012, pp. 2021-2024. [PDF]