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Found 7 papers, 2 papers with code
Multitask 3D CBCT-to-CT Translation and Organs-at-Risk Segmentation Using Physics-Based Data Augmentation
Treatment planning is done once at the beginning of the treatment using high-quality planning CT (pCT) images and manual contours for organs-at-risk (OARs) structures.
A feature-supervised generative adversarial network for environmental monitoring during hazy days
First, pairs of hazy and clean images are used as inputs to supervise the encoding process and obtain high-quality feature maps.
Generalizable Cone Beam CT Esophagus Segmentation Using Physics-Based Data Augmentation
Automated segmentation of esophagus is critical in image guided/adaptive radiotherapy of lung cancer to minimize radiation-induced toxicities such as acute esophagitis.
Joint Embedding in Named Entity Linking on Sentence Level
The named entity linking is challenging, given the fact that there are multiple candidate entities for a mention in a document.
A Poisson-Gaussian Denoising Dataset with Real Fluorescence Microscopy Images
In this paper, we fill this gap by constructing a dataset - the Fluorescence Microscopy Denoising (FMD) dataset - that is dedicated to Poisson-Gaussian denoising.
Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation
Our approach needs only 3D bounding boxes for all instances and full voxel annotation for a small fraction of the instances, and uses a novel two-stage 3D instance segmentation model utilizing these two kinds of annotation, respectively.
Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
Image segmentation is a fundamental problem in biomedical image analysis.
