周元品Yuanpin Zhou, Ph.D.

工作经历

教育背景

项目经历

学术成果

期刊论文 6 篇 · 会议论文 11 篇 · 专著 1 章 · 发明专利 2 项 · 软件著作权 1 项 · Google Scholar 完整列表

期刊论文

1. J. Luo, Y. Li, Y. Zhou, S. Che, X. Ding, Z. Zhang, and Y. Lu*. VQ-CSDN: A Vector Quantized Content-Stain Decoupling Network for Stain Normalization of H&E Histopathology Images. IEEE Journal of Biomedical and Health Informatics, 2026.
2. Y. Tang#, Y. Zhou#, S. Zhang, and Y. Lu*. A High-Resolution Digital Pathological Image Staining Style Transfer Model Based on Gradient Guidance. Bioengineering, vol. 12, no. 2, p. 187, 2025.
3. Y. Zhou#, S. Che#, F. Lu, S. Liu, Z. Yan, J. Wei, Y. Li, X. Ding, and Y. Lu*. Iterative Multiple Instance Learning for Weakly Annotated Whole Slide Image Classification. Physics in Medicine and Biology, vol. 68, no. 15, p. 155007, 2023.
4. G. Jiang#, Z. He#, Y. Zhou#, J. Wei, Y. Xu, H. Zeng, J. Wu, G. Qin, W. Chen*, and Y. Lu*. Multi-scale Cascaded Networks for Synthesis of Mammogram to Decrease Intensity Distortion and Increase Perceptual Similarity. Medical Physics, vol. 50, no. 2, pp. 837–853, 2023.
5. Y. Zhou, J. Wei*, D. Wu*, and Y. Zhang*. Generating Full-Field Digital Mammogram from Digitized Screen-Film Mammogram for Breast Cancer Screening with High-Resolution Generative Adversarial Network. Frontiers in Oncology, vol. 12, p. 868257, 2022.
6. G. Cai, Y. Guo, H. Zeng, W. Chen, Y. Zhou, and Y. Lu*. Computer-aided Detection and Diagnosis of Microcalcification Clusters on Full Field Digital Mammograms Based on Deep Learning Method Using Neutrosophic Boosting. Multimedia Tools and Applications, vol. 79, no. 23, pp. 17147–17167, 2020.

会议论文

1. J. Luo, Y. Zhou, S. Che, X. Ding, Z. Zhang, and Y. Lu*. Vector Quantized Stain Disentanglement Network for Stain Normalization of H&E-Stained Pathological Images. ICASSP 2026 – 2026 IEEE International Conference on Acoustics, Speech and Signal Processing, 2026.
2. H. Jiang, Q. Liu, Y. Zhou, J. Pan, T. Song, and Y. Lu*. Anatomy-Guided Multitask Learning for MRI-Based Classification of Placenta Accreta Spectrum and its Subtypes. 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 2025, pp. 1–5.
3. Y. Zhou, and H. Wang*. Divide and Conquer Radiology Report Generation via Observation Level Fine-grained Pretraining and Prompt Tuning. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
4. Y. Zhou#, H. Wang#, Y. Bai, Y. Wan, C. Jin, M. Chen, and X. Teng*. Digital Pathology Image Deblurring via Local Focus Quality Assessment. ICASSP 2024 – 2024 IEEE International Conference on Acoustics, Speech and Signal Processing, 2024.
5. Y. Zhou, and Y. Lu*. Multiple Instance Learning with Critical Instance for Whole Slide Image Classification. 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), Cartagena de Indias, Colombia, 2023, pp. 1–5.
6. Y. Zhou, and Y. Lu*. Multiple Instance Learning with Task-Specific Multi-Level Features for Weakly Annotated Histopathological Image Classification. ICASSP 2022 – 2022 IEEE International Conference on Acoustics, Speech and Signal Processing, Singapore, 2022, pp. 1366–1370.
7. Y. Zhou, and Y. Lu*. Deep Hierarchical Multiple Instance Learning for Whole Slide Image Classification. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), Kolkata, India, 2022, pp. 1–4.
8. Y. Zhou, J. Wei, M. A. Helvie, H. Chan, C. Zhou, L. Hadjiiski, and Y. Lu*. Generating High Resolution Digital Mammogram from Digitized Film Mammogram with Conditional Generative Adversarial Network. Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 1131426, 2020.
9. G. Cai, Y. Guo, W. Chen, H. Zeng, Y. Zhou, and Y. Lu*. Computer-aided Detection and Classification of Microcalcification Clusters on Full Field Digital Mammograms Using Deep Convolution Neural Network. Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109502J, 2019.
10. G. Cai, Y. Guo, Y. Zhang, G. Qin, Y. Zhou, and Y. Lu*. A Fully Automatic Microcalcification Detection Approach Based on Deep Convolution Neural Network. Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105752Q, 2018.
11. C. Xu, Y. Lu, Y. Zhou*. An Automatic Visible Watermark Removal Technique Using Image Inpainting Algorithms. 2017 4th International Conference on Systems and Informatics (ICSAI), Hangzhou, China, 2017, pp. 1152–1157.

专著

1. G. Cai, Y. Guo, W. Chen, H. Zeng, Y. Zhou, and Y. Lu. Chapter 14 – Neutrosophic Set-based Deep Learning in Mammogram Analysis. Neutrosophic Set in Medical Image Analysis. Academic Press, 2019, pp. 287–310.

发明专利

1. 陆遥，周元品。一种基于图像修复的自动水印去除方法。专利号：ZL 2017 1 0153491.7（已转让）。
2. 陆遥，江功发，周元品。一种全数字化乳腺摄影图像合成方法、系统、设备及介质。公开号：CN114418916A。

软件著作权登记

1. 基于图像修复算法的自动去水印软件 V1.0。登记号：2018SR964535。

技能