4 citations · 4 across the 2 of their papers we have counts for
5 papers
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…
Diagnosis Of Takotsubo Syndrome By Robust Feature Selection From The Complex Latent Space Of DL-based Segmentation Network
Fahim Ahmed Zaman, Wahidul Alam, Tarun Kanti Roy +3
Researchers have shown significant correlations among segmented objects in various medical imaging modalities and disease related pathologies. Several studies showed that using han…
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…
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…
Globally Optimal Segmentation of Mutually Interacting Surfaces using Deep Learning
Hui Xie, Zhe Pan, Leixin Zhou +5
Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary and mutual influence between adjacent ob…