2023 A Regional-Attentive Multi-Task Learning Framework for Breast Ultrasound Image Segmentation and Classification Meng Xu, Kuan Huang, and Xiaojun Qi IEEE Access, 2023 Bib HTML PDF @article{xu2023regional, title = {A Regional-Attentive Multi-Task Learning Framework for Breast Ultrasound Image Segmentation and Classification}, author = {Xu, Meng and Huang, Kuan and Qi, Xiaojun}, journal = {IEEE Access}, year = {2023}, publisher = {IEEE}, } 2022 ISBI Multi-task learning with context-oriented self-attention for breast ultrasound image classification and segmentation Meng Xu, Kuan Huang, and Xiaojun Qi In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022 Bib HTML @inproceedings{xu2022multi, title = {Multi-task learning with context-oriented self-attention for breast ultrasound image classification and segmentation}, author = {Xu, Meng and Huang, Kuan and Qi, Xiaojun}, booktitle = {2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)}, pages = {1--5}, year = {2022}, organization = {IEEE}, } BUSIS: a benchmark for breast ultrasound image segmentation Yingtao Zhang, Min Xian, Heng-Da Cheng, and 7 more authors In Healthcare, 2022 Bib HTML @inproceedings{zhang2022busis, title = {BUSIS: a benchmark for breast ultrasound image segmentation}, author = {Zhang, Yingtao and Xian, Min and Cheng, Heng-Da and Shareef, Bryar and Ding, Jianrui and Xu, Fei and Huang, Kuan and Zhang, Boyu and Ning, Chunping and Wang, Ying}, booktitle = {Healthcare}, volume = {10}, number = {4}, pages = {729}, year = {2022}, organization = {MDPI}, } Trustworthy Breast Ultrasound Image Semantic Segmentation Based on Fuzzy Uncertainty Reduction Kuan Huang, Yingtao Zhang, Heng-Da Cheng, and 1 more author In Healthcare, 2022 Bib HTML @inproceedings{huang2022trustworthy, title = {Trustworthy Breast Ultrasound Image Semantic Segmentation Based on Fuzzy Uncertainty Reduction}, author = {Huang, Kuan and Zhang, Yingtao and Cheng, Heng-Da and Xing, Ping}, booktitle = {Healthcare}, volume = {10}, number = {12}, pages = {2480}, year = {2022}, organization = {MDPI}, } BIBM Weakly Unpaired Image Translation from Hematoxylin and Eosin Staining Image to Immunohistochemistry Staining Image Kuan Huang, Yifei Cheng, Qiang Gao, and 1 more author In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022 Bib HTML @inproceedings{huang2022weakly, title = {Weakly Unpaired Image Translation from Hematoxylin and Eosin Staining Image to Immunohistochemistry Staining Image}, author = {Huang, Kuan and Cheng, Yifei and Gao, Qiang and Zhang, Bing}, booktitle = {2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)}, pages = {1013--1019}, year = {2022}, organization = {IEEE}, } BIBM A Deep Active Learning Framework with Information Guided Label Generation for Medical Image Segmentation Kuan Huang, Jianhua Huang, Weichen Wang, and 2 more authors In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022 Bib HTML @inproceedings{huang2022deep, title = {A Deep Active Learning Framework with Information Guided Label Generation for Medical Image Segmentation}, author = {Huang, Kuan and Huang, Jianhua and Wang, Weichen and Xu, Meng and Liu, Feifei}, booktitle = {2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)}, pages = {1562--1567}, year = {2022}, organization = {IEEE}, } 2021 Breast Ultrasound Image Segmentation Based on Uncertainty Reduction and Context Information Kuan Huang Utah State University, 2021 Bib HTML @phdthesis{huang2021breast, title = {Breast Ultrasound Image Segmentation Based on Uncertainty Reduction and Context Information}, author = {Huang, Kuan}, year = {2021}, school = {Utah State University}, } ICPR Semantic Segmentation of Breast Ultrasound Image with Pyramid Fuzzy Uncertainty Reduction and Direction Connectedness Feature Kuan Huang, Yingtao Zhang, Heng-Da Cheng, and 2 more authors In 2020 25th International Conference on Pattern Recognition (ICPR), 2021 Bib HTML @inproceedings{huang2021semantic, title = {Semantic Segmentation of Breast Ultrasound Image with Pyramid Fuzzy Uncertainty Reduction and Direction Connectedness Feature}, author = {Huang, Kuan and Zhang, Yingtao and Cheng, Heng-Da and Xing, Ping and Zhang, Boyu}, booktitle = {2020 25th International Conference on Pattern Recognition (ICPR)}, pages = {3357--3364}, year = {2021}, organization = {IEEE}, } ISBI Mssa-net: Multi-scale self-attention network for breast ultrasound image segmentation Meng Xu, Kuan Huang, Qiuxiao Chen, and 1 more author In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021 Bib HTML @inproceedings{xu2021mssa, title = {Mssa-net: Multi-scale self-attention network for breast ultrasound image segmentation}, author = {Xu, Meng and Huang, Kuan and Chen, Qiuxiao and Qi, Xiaojun}, booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)}, pages = {827--831}, year = {2021}, organization = {IEEE}, } ICME Shape-adaptive convolutional operator for breast ultrasound image segmentation Kuan Huang, Yingtao Zhang, Heng-Da Cheng, and 1 more author In 2021 IEEE International Conference on Multimedia and Expo (ICME), 2021 Bib HTML @inproceedings{huang2021shape, title = {Shape-adaptive convolutional operator for breast ultrasound image segmentation}, author = {Huang, Kuan and Zhang, Yingtao and Cheng, Heng-Da and Xing, Ping}, booktitle = {2021 IEEE International Conference on Multimedia and Expo (ICME)}, pages = {1--6}, year = {2021}, organization = {IEEE}, } Semantic segmentation of breast ultrasound image with fuzzy deep learning network and breast anatomy constraints Kuan Huang, Yingtao Zhang, Heng-Da Cheng, and 2 more authors Neurocomputing, 2021 Bib HTML @article{huang2021semantid, title = {Semantic segmentation of breast ultrasound image with fuzzy deep learning network and breast anatomy constraints}, author = {Huang, Kuan and Zhang, Yingtao and Cheng, Heng-Da and Xing, Ping and Zhang, Boyu}, journal = {Neurocomputing}, volume = {450}, pages = {319--335}, year = {2021}, publisher = {Elsevier}, } EMBC MSF-GAN: Multi-Scale Fuzzy Generative Adversarial Network for Breast Ultrasound Image Segmentation Kuan Huang, Yingtao Zhang, Heng-Da Cheng, and 1 more author In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021 Bib HTML @inproceedings{huang2021msf, title = {MSF-GAN: Multi-Scale Fuzzy Generative Adversarial Network for Breast Ultrasound Image Segmentation}, author = {Huang, Kuan and Zhang, Yingtao and Cheng, Heng-Da and Xing, Ping}, booktitle = {2021 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)}, pages = {3193--3196}, year = {2021}, organization = {IEEE}, } EMBC Interpretable fine-grained BI-RADS classification of breast tumors Yi Xiao, Kuan Huang, Sihua Niu, and 1 more author In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021 Bib HTML @inproceedings{xiao2021interpretable, title = {Interpretable fine-grained BI-RADS classification of breast tumors}, author = {Xiao, Yi and Huang, Kuan and Niu, Sihua and Huang, Jianhua}, booktitle = {2021 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)}, pages = {3617--3621}, year = {2021}, organization = {IEEE}, } EMBC NGMMs: Neutrosophic Gaussian Mixture Models for Breast Ultrasound Image Classification Kuan Huang, Meng Xu, and Xiaojun Qi In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021 Bib HTML @inproceedings{huang2021ngmms, title = {NGMMs: Neutrosophic Gaussian Mixture Models for Breast Ultrasound Image Classification}, author = {Huang, Kuan and Xu, Meng and Qi, Xiaojun}, booktitle = {2021 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)}, pages = {3943--3947}, year = {2021}, organization = {IEEE}, } 2019 Preliminary results of computer-aided diagnosis for magnetic resonance imaging of solid breast lesions Qiujie Yu, Kuan Huang, Ye Zhu, and 2 more authors Breast Cancer Research and Treatment, 2019 Bib HTML @article{yu2019preliminary, title = {Preliminary results of computer-aided diagnosis for magnetic resonance imaging of solid breast lesions}, author = {Yu, Qiujie and Huang, Kuan and Zhu, Ye and Chen, Xiaodan and Meng, Wei}, journal = {Breast Cancer Research and Treatment}, volume = {177}, pages = {419--426}, year = {2019}, publisher = {Springer}, } 2018 arXiv Computer-aided knee joint magnetic resonance image segmentation-a survey Boyu Zhang, Yingtao Zhang, Heng-Da Cheng, and 4 more authors arXiv preprint arXiv:1802.04894, 2018 Bib HTML @article{zhang2018computer, title = {Computer-aided knee joint magnetic resonance image segmentation-a survey}, author = {Zhang, Boyu and Zhang, Yingtao and Cheng, Heng-Da and Xian, Min and Gai, Shan and Cheng, Olivia and Huang, Kuan}, journal = {arXiv preprint arXiv:1802.04894}, year = {2018}, } ICPR A hybrid framework for tumor saliency estimation Fei Xu, Min Xian, Yingtao Zhang, and 6 more authors In 2018 24th International Conference on Pattern Recognition (ICPR), 2018 Bib HTML @inproceedings{xu2018hybrid, title = {A hybrid framework for tumor saliency estimation}, author = {Xu, Fei and Xian, Min and Zhang, Yingtao and Huang, Kuan and Cheng, Heng-Da and Zhang, Boyu and Ding, Jianrui and Ning, Chunping and Wang, Ying}, booktitle = {2018 24th International Conference on Pattern Recognition (ICPR)}, pages = {3935--3940}, year = {2018}, organization = {IEEE}, } ICPR Medical knowledge constrained semantic breast ultrasound image segmentation Kuan Huang, Heng-Da Cheng, Yingtao Zhang, and 3 more authors In 2018 24th International Conference on Pattern Recognition (ICPR), 2018 Bib HTML @inproceedings{huang2018medical, dimensions = {true}, title = {Medical knowledge constrained semantic breast ultrasound image segmentation}, author = {Huang, Kuan and Cheng, Heng-Da and Zhang, Yingtao and Zhang, Boyu and Xing, Ping and Ning, Chunping}, booktitle = {2018 24th International Conference on Pattern Recognition (ICPR)}, pages = {1193--1198}, year = {2018}, organization = {IEEE}, }