✨26/7/2023 Delivered a lecture at the Cambridge Mathematics of Information in Healthcare Hub at the Centre for Mathematical Sciences on "Annotation and Practical Problems in Deep Learning based Computational Pathology".
✨16/7/2023 Gave a keynote speech at the 10th Medical Imaging Computing Seminar (MICS) on "Research on Pathological Image Annotation and Clinical Application Problems Based on Deep Learning".
✨03/7/2023 Participated in the 2nd Shanghai Jiao Tong University Artificial Intelligence Exhibition, presenting a video exhibition on "Efficient Diagnosis of Thyroid Cytopathology Images by Artificial Intelligence".
✨24/6/2023 Had 4 papers accepted at the 2023 Medical Image Computing and Computer-Assisted Intervention(MICCAI).
1) J Ke, K Liu, Y Sun, Y Xue, J Huang, Y Lu, J Dai, Y Chen, X Han, Y Shen, D Shen. Artifact Detection and Restoration in Histology Images with Stain-Style and Structural Preservation. IEEE Transactions on Medical Imaging (TMI).
2) J Ke, Y Lu, Y Shen, J Zhu, Y Zhou, J Huang, J Yao, X Liang, Y Guo, Z Wei, S Liu, Q Huang, F Jiang & D Shen. A crowd cluster pinpointed nucleus segmentation framework with cross-modality datasets. Medical Image Analysis (MedIA), 2023, 85(102758).
3) Y Li, Y Shen, J Zhang, S Song, Z Li, J Ke, D Shen. A Hierarchical Graph V-Net with Semi-supervised Pre-training for Histological Image based Breast Cancer Classification. IEEE Transactions on Medical Imaging (TMI).
4) J Ke, Y Shen, Y Lu, Y Guo & D Shen. Mine Local Homogeneous Representation by Interaction Information Clustering with Unsupervised Learning in Histopathology Images. Computer Methods and Programs in Biomedicine.
5) Y Shen, A Sowmya, Y Luo, X Liang, D Shen & J Ke. A Federated Learning System for Histopathology Image Analysis with an Orchestral Stain-Normalization GAN, IEEE Transactions on Medical Imaging (TMI).
6) Y Shen, D Shen & J Ke. Identify Representative Samples by Conditional Random Field of Cancer Histology Images, IEEE Transactions on Medical Imaging (TMI), Volume: 41, Issue: 12, December 2022.
7) Y Shen & J Ke. Sampling Based Tumor Recognition in Whole-slide Histology Image with Deep Learning Approaches. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume: 19, Issue: 4, 2022, pp: 2431 – 2441.
8) J Ke, Y Shen, Y Lu, J Deng, J. D. Wright, Y Zhang, Q Huang, D Wang, N Jing, X Liang & F Jiang. Quantitative analysis of abnormalities in gynecologic cytopathology with deep learning, Laboratory Investigation 101, pp: 513–524, 2021.
9) M Liu, Y Liu, P Xu, H Cui, J Ke & J Ma. Exploiting Geometric Features via Hierarchical Graph Pyramid Transformer for Cancer Diagnosis using Histopathological Images. IEEE Transactions on Medical Imaging(TMI).
10) C Wang, S Li, J Ke, C Zhang & Y Shen. RandStainNA++: Enhance Random Stain Augmentation and Normalization through Foreground and Background Differentiation. IEEE Journal of Biomedical and Health Informatics(JBHI).
1) J Wang, F Ino & J Ke. PRF: A Fast Parallel Relaxed Flooding Algorithm for Voronoi Diagram Generation on GPU. 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2023.
2) J Zhu, Y Shen, H Zhang & J Ke. An Anti-Biased TBSRTC-Category Aware Nuclei Segmentation Framework with A Multi-Label Thyroid Cytology Benchmark, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023.
3) E L Carbonell, Y Shen, X Yang & J Ke. COVID-19 Pneumonia Classification with Transformer from Incomplete Modalities. MICCAI 2023.
4) Y Shen & J Ke. StainDiff: Transfer Stain Styles of Histology Images with Denoising Diffusion Probabilistic Models and Self-Ensemble. MICCAI 2023.
5) Y Shen, Y Luo, D Shen & J Ke. RandStainNA: Learning Stain-Agnostic Features from Histology Slides by Bridging Stain Augmentation and Normalization, MICCAI 2022.
6) J Ke, Y Shen, X Liang, D Shen. Contrastive Learning Based Stain Normalization Across Multiple Tumor Histopathology. MICCAI 2021.
7) Y Shen & J Ke. Su-Sampling Based Active Learning For Large-Scale Histopathology Image. International Conference on Image Processing (ICIP), 2021.
8) J Huang, Y Shen, D Shen & J Ke. CA2.5-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection. MICCAI 2021.
9) Y Shen, Y Lu, Y Luo & J Ke. Cluster Image Patches with Multiple Mutual Information in Unlabelled Whole-Slide Image. International Conference on Bioinformatics and Biomedicine (BIBM) 2021
10) Z Song, F Wu, X Liu, J Ke, N Jing & X Liang. VR-DANN: Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration, the 53rd IEEE/ACM International Symposium on Microarchitecture (MICRO) 2020.
11) X Song, J Wang, T Li, L Jiang, J Ke, X Liang & N Jing. GPNPU: Enabling Efficient Hardware-Based Direct Convolution with Multi-Precision Support in GPU Tensor Cores. the 57th ACM/IEEE Design Automation Conference (DAC) 2020.
12) Y Shen & J Ke. A Deformable CRF Model for Histopathology Whole-slide Image Classification. MICCAI 2020.
13) J Ke, Y Shen, Jason D. Wright, N Jing, X Liang & D Shen. Identifying patch-level MSI from histological images of Colorectal Cancer by a Knowledge Distillation Model. BIBM 2020
14) J Ke, Yiqing Shen, Yi Guo & Xiaoyao Liang. Fast Tumor Detector in Whole-slide Image with Dynamic Programming Based Monte Carlo Sampling, International Conference on Image Processing (ICIP), 2020.
景乃锋,柯晶,梁晓峣。通用图形处理器设计-GPGPU编程模型与架构原理,清华大学出版社,2022-05出版
国家自然科学基金青年:弱标注肿瘤病理图像分析及异构系统高通量计算关键技术研究 2022.1~2024.12
上海市自然科学基金面上项目:基于临床癌症辅助诊断的病理图像空间关联性特征融合研究 2023.4~2026.3
上海交通大学“交大之星“计划医工交叉研究基金:2023.1~2025.12
a)基于人工智能的多模态影像构建肝癌门脉癌栓的新型精准分型
b)基于深度学习的多模态多切面超声及病理图像分析早期评估乳腺癌新辅助化疗疗效
细胞病理图像分割方法及装置; ZL202011379134.0;授权公告日, 2022-11-01
病理图像染色风格归一化方法及装置;ZL202010912039.6;授权公告日:2022-11-01
图像分类方法、装置、电子设备和存储介质;ZL202110510967.4;授权公告日:2021-5-11
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