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Found 11 papers, 7 papers with code
Biomedical image analysis competitions: The state of current participation practice
Of these, 84% were based on standard architectures.
Learning to segment from object sizes
We propose an algorithm for training a deep segmentation network from a dataset of a few pixel-wise annotated images and many images with known object sizes.
Fast learning from label proportions with small bags
In learning from label proportions (LLP), the instances are grouped into bags, and the task is to learn an instance classifier given relative class proportions in training bags.
Automatic evaluation of human oocyte developmental potential from microscopy images
Infertility is becoming an issue for an increasing number of couples.
Benchmarking of image registration methods for differently stained histological slides
Image registration is a common task for many biomedical analysis applications.
Region growing using superpixels with learned shape prior.
Region growing is a classical image segmentation method based on hierarchical region aggregation using local similarity rules.
Supervised and unsupervised segmentation using superpixels, model estimation, and Graph Cut.
Image segmentation is widely used as an initial phase of many image analysis tasks.
Detection and Localization of Drosophila Egg Chambers in Microscopy Images.
Drosophila melanogaster is a well-known model organism that can be used for studying oogenesis (egg chamber development) including gene expression patterns.
Binary Pattern Dictionary Learning for Gene Expression Representation in Drosophila Imaginal Discs.
The key part of our work is a binary pattern dictionary learning algorithm, that takes a set of binary images and determines a set of patterns, which can be used to represent the input images with a small error.
Reconstructing Evolving Tree Structures in Time Lapse Sequences
We propose an approach to reconstructing tree structures that evolve over time in 2D images and 3D image stacks such as neuronal axons or plant branches.
Consistent and elastic registration of histological sections using vector-spline regularization
Here we present a new image registration algorithm for the alignment of histological sections that combines the ideas of B-spline based elastic registration and consistent image registration, to allow simultaneous registration of images in two directions (direct and inverse).
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