4 citations · 5 across the 3 of their papers we have counts for
5 papers
A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging
Davood Karimi, Lana Vasung, Camilo Jaimes +4
Multi-compartment modeling of diffusion-weighted magnetic resonance imaging measurements is necessary for accurate brain connectivity analysis. Existing methods for estimating the…
Sparse and redundant signal representations for x-ray computed tomography
Davood Karimi
Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselv…
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Davood Karimi, Haoran Dou, Simon K. Warfield +1
Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However…
Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks
Davood Karimi, Septimiu E. Salcudean
The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation methods. However, existing segmentation methods do not attempt to reduce HD directly. In this pa…
A deep learning-based method for prostate segmentation in T2-weighted magnetic resonance imaging
Davood Karimi, Golnoosh Samei, Yanan Shao +1
We propose a novel automatic method for accurate segmentation of the prostate in T2-weighted magnetic resonance imaging (MRI). Our method is based on convolutional neural networks…