TU5.PB.11
AFMUNet: Adaptive Filter-Based Frequency Modulation UNet for OCTA Segmentation
Ibrahim Abdelhalim, Mohamed Elsharkawy, University of Louisville, United States; Fatma Taher, Ashraf Khalil, Zayed University, United Arab Emirates; Mohammed Ghazal, Abu Dhabi University, United Arab Emirates; Ali Mahmoud, Ayman El-Baz, University of Louisville, United States
Session:
TU5.PB: Biomedical Signal and Image Processing 4 Poster
Track:
[BI] Biomedical Signal and Image Processing
Location:
Poster Area B
Presentation Time:
Tue, 16 Sep, 16:30 - 18:00 Anchorage Time (UTC -8)
Session Chair:
Anwaar Ulhaq, Central Queensland University, Sydney, Australia
Presentation
Discussion
Resources
No resources available.
Session TU5.PB
TU5.PB.1: DIFFUSION-BASED CT IMAGE SEGMENTATION FOR INTRACEREBRAL HEMORRHAGE
Lili Wang, Pingping Cai, Zhuangzhuang Gu, Srihari Nelakuditi, Yan Tong, University of South Carolina, United States
TU5.PB.2: CYTOFUSION: A LATENT DIFFUSION-BASED FRAMEWORK FOR CYTOLOGY CLASSIFICATION
Linyi Qian, Qian Huang, Yulin Chen, Shaoling Qin, Hohai University, China
TU5.PB.3: DP-Net: A 3D Dilated Projection Framework for Precise Fetal Brain Tissue Segmentation
Junpeng Tan, Mingjin Chen, Chunmei Qing, Xin Zhang, Xiangmin Xu, South China University of Technology, China
TU5.PB.4: DIFFUSION BASED SHAPE-AWARE LEARNING WITH MULTI-SCALE CONTEXT FOR SEGMENTATION OF TIBIOFEMORAL KNEE JOINT TISSUES: AN END-TO-END APPROACH
Akshay Daydar, Alik Pramanick, Arijit Sur, Subramani Kanagaraj, Indian Institute of Technology Guwahati, India
TU5.PB.5: A Generative Diffusion Model to solve Inverse Problems for Robust in-NICU Neonatal MRI
Yamin Arefeen, Brett Levac, Jonathan Tamir, The University of Texas at Austin, United States
TU5.PB.6: A MULTISCALE ATTENTION-BASED DEEP LEARNING METHOD FOR DCE-MRI BREAST TUMOR SEGMENTATION
Pablo Giaccaglia, Isabella Poles, Valentina Lidoni, Politecnico di Milano, Italy; Veronica Rizzo, Sapienza University of Rome, Italy; Michele Gentili, Mass General Brigham Hospital and Harvard Medical School, United States; Federica Pediconi, Sapienza University of Rome, Italy; Marco Domenico Santambrogio, Politecnico di Milano, Italy; Eleonora D'Arnese, University of Edinburgh, United Kingdom
TU5.PB.7: Investigating Data Replication in Medical Synthetic Image Generation with Diffusion Models
Aimon Rahman, Jeya Maria Jose Valanarasu, Vishal M. Patel, Johns Hopkins University, United States
TU5.PB.8: ONE-STAGE FRAMEWORK FOR THYROID NODULE DETECTION WITH MIXUP AND NEGATIVE SAMPLE UTILIZATION
Yuxuan He, Qilei Chen, Zinan Xiong, Xiaolong Liang, Yu Cao, Benyuan Liu, University of Massachusetts Lowell, United States
TU5.PB.9: Segmentation for Early Tumor Detection in Mammograms via Temporal Discrepancy Analysis and Dynamic Loss Weighting
Afsana Ahsan Jeny, Sahand Hamzehei, Mostafa Karami, University of Connecticut, United States; Stephen Andrew Baker, Tucker Van Rathe, Clifford Yang, University of Connecticut Health, United States; Sheida Nabavi, University of Connecticut, United States
TU5.PB.10: ADVANCEMENTS IN MEDICAL IMAGE CLASSIFICATION THROUGH FINE-TUNING NATURAL DOMAIN FOUNDATION MODELS
Mobina Mansoori, Sajjad Shahabodini, Farnoush Bayatmakou, Concordia University, Canada; Jamshid Abouei, Yazd University, Iran; Konstantinos Plataniotis, University of Toronto, Canada; Arash Mohammadi, Concordia University, Canada
TU5.PB.11: AFMUNet: Adaptive Filter-Based Frequency Modulation UNet for OCTA Segmentation
Ibrahim Abdelhalim, Mohamed Elsharkawy, University of Louisville, United States; Fatma Taher, Ashraf Khalil, Zayed University, United Arab Emirates; Mohammed Ghazal, Abu Dhabi University, United Arab Emirates; Ali Mahmoud, Ayman El-Baz, University of Louisville, United States
TU5.PB.12: ORGANOID-ICLIP: CLASS IMBALANCE-AWARE VISION-LANGUAGE LEARNING FOR ORGANOID MITOSIS CLASSIFICATION
Anabia Sohail, Khalifa University, United Arab Emirates; Oishi Deb, University of Oxford, UK, United Kingdom; Anwaar Ulhaq, Central Queensland University, Sydney, Australia, United Kingdom
Contacts