Developing a Novel Image Marker to Predict the Responses of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer Patients

no code implementations • 13 Sep 2023 • Ke Zhang, Neman Abdoli, Patrik Gilley, Youkabed Sadri, Xuxin Chen, Theresa C. Thai, Lauren Dockery, Kathleen Moore, Robert S. Mannel, Yuchen Qiu

To address this clinical challenge, the purpose of this study is to develop a novel image marker to achieve high accuracy response prediction of the NACT at an early stage.

Evaluating the Effectiveness of 2D and 3D Features for Predicting Tumor Response to Chemotherapy

no code implementations • 28 Mar 2023 • Neman Abdoli, Ke Zhang, Patrik Gilley, Xuxin Chen, Youkabed Sadri, Theresa C. Thai, Lauren E. Dockery, Kathleen Moore, Robert S. Mannel, Yuchen Qiu

2D and 3D tumor features are widely used in a variety of medical image analysis tasks.

Decision Making

Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms

no code implementations • 21 Jun 2022 • Xuxin Chen, Ke Zhang, Neman Abdoli, Patrik W. Gilley, Ximin Wang, Hong Liu, Bin Zheng, Yuchen Qiu

For this purpose, we employ local Transformer blocks to separately learn patch relationships within four mammograms acquired from two-view (CC/MLO) of two-side (right/left) breasts.

Image Registration