NEWS

[NEWS 2024/11/10] One research work has been accepted in ML4H 2024 (finding track)

• Seong Je Oh*, Kyungsu Kim*†, Ju Hwan Lee, Chae Yeon Lim, Tae Uk Kim, Myung Jin Chung†, "Enhancing Generative Networks for Chest Anomaly Localization through Automatic Registration-Based Unpaired-to-Pseudo-Paired Training Data Translation"

  • Seong Je Oh have led this project as the co-first author (Congratulations!).

  • Collaboration with Samsung Medical Center

[NEWS 2024/11/10] Two research works were accepted in RSNA 2024 (2024/12/01)

• Kyungsu Kim, Adham Alkhadrawi, Synho Do, Manisha Bahl†, "Preoperative Prediction of Ductal Carcinoma in Situ Upgrade Risk Using Mammographic Imaging" [Oral Presentation]

  • Coworked with MGH and Harvard Medical School & Kempner AI Institute at Harvard University

• Kyungsu Kim, Manisha Bahl, Saul Langarica, Synho Do†, "Refining Microcalcification Detection in Full-field Digital Mammography Using Generative AI: Enhanced Accuracy and Reduced False Positives"

  • Coworked with MGH and Harvard Medical School & Kempner AI Institute at Harvard University

[NEWS 2024/10/07] Two papers were published in ECCV 2024

• Sanghyun Jo, Fei Pan, In-Jae Yu, Kyungsu Kim† , "DHR: Enhancing Weakly Supervised Semantic Segmentation with Hierarchical Spatial-Class Rebalancing"

  • Sanghyun Jo have led this project as the first author (Congratulations!).

  • Collaboration with University of Michigan 

• Sanghyun Jo∗ , Soohyun Ryu∗ , Sungyub Kim, Eunho Yang, Kyungsu Kim† , "TTD: TextTag Distillation For Open-Vocabulary Classification and Segmentation"

  • Sanghyun Jo and Soohyun Ryu have led this project as the co-first author (Congratulations!).

  • Collaboration with KAIST AI