AIMC Journal:
Medical image analysis
Showing 451 to 460 of 684 articles
Local rotation invariance in 3D CNNs.
Medical image analysis
Jun 20, 2020
Locally Rotation Invariant (LRI) image analysis was shown to be fundamental in many applications and in particular in medical imaging where local structures of tissues occur at arbitrary rotations. LRI constituted the cornerstone of several breakthro...
Self-co-attention neural network for anatomy segmentation in whole breast ultrasound.
Medical image analysis
Jun 12, 2020
The automated whole breast ultrasound (AWBUS) is a new breast imaging technique that can depict the whole breast anatomy. To facilitate the reading of AWBUS images and support the breast density estimation, an automatic breast anatomy segmentation me...
Subsampled brain MRI reconstruction by generative adversarial neural networks.
Medical image analysis
Jun 11, 2020
A main challenge in magnetic resonance imaging (MRI) is speeding up scan time. Beyond improving patient experience and reducing operational costs, faster scans are essential for time-sensitive imaging, such as fetal, cardiac, or functional MRI, where...
Uncertainty-aware domain alignment for anatomical structure segmentation.
Medical image analysis
Jun 9, 2020
Automatic and accurate segmentation of anatomical structures on medical images is crucial for detecting various potential diseases. However, the segmentation performance of established deep neural networks may degenerate on different modalities or de...
Graph refinement based airway extraction using mean-field networks and graph neural networks.
Medical image analysis
Jun 9, 2020
Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-trees from image data by, first deriving a graph-based representation o...
Deep learning with 4D spatio-temporal data representations for OCT-based force estimation.
Medical image analysis
May 23, 2020
Estimating the forces acting between instruments and tissue is a challenging problem for robot-assisted minimally-invasive surgery. Recently, numerous vision-based methods have been proposed to replace electro-mechanical approaches. Moreover, optical...
Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data.
Medical image analysis
May 19, 2020
PURPOSE: Attenuation correction (AC) is essential for quantitative PET imaging. In the absence of concurrent CT scanning, for instance on hybrid PET/MRI systems or dedicated brain PET scanners, an accurate approach for synthetic CT generation is high...
DeepDistance: A multi-task deep regression model for cell detection in inverted microscopy images.
Medical image analysis
May 11, 2020
This paper presents a new deep regression model, which we call DeepDistance, for cell detection in images acquired with inverted microscopy. This model considers cell detection as a task of finding most probable locations that suggest cell centers in...
The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study.
Medical image analysis
May 1, 2020
Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with ima...
DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images.
Medical image analysis
Apr 30, 2020
Diabetic retinopathy (DR) grading is crucial in determining the adequate treatment and follow up of patient, but the screening process can be tiresome and prone to errors. Deep learning approaches have shown promising performance as computer-aided di...
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