3 papers
cs.CV2024
Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracy
Fahim Ahmed Zaman, Mathews Jacob, Amanda Chang +3
Diffusion Probabilistic Models (DPMs) suffer from inefficient inference due to their slow sampling and high memory consumption, which limits their applicability to various medical…
eess.IV2023
Surf-CDM: Score-Based Surface Cold-Diffusion Model For Medical Image Segmentation
Fahim Ahmed Zaman, Mathews Jacob, Amanda Chang +3
Diffusion models have shown impressive performance for image generation, often times outperforming other generative models. Since their introduction, researchers have extended the…
cs.CV2023
Trust, but Verify: Robust Image Segmentation using Deep Learning
Fahim Ahmed Zaman, Xiaodong Wu, Weiyu Xu +2
We describe a method for verifying the output of a deep neural network for medical image segmentation that is robust to several classes of random as well as worst-case perturbation…