Search Results for "image analysis"

Gravitropic response is studied in most of the laboratories working with Arabidopsis thaliana, for example, to detect new phenotypes in mutants. However, manual analysis of images and microscopy data are known to be subjected to human bias. This is particularly the case for manual measurements of root bending as the angle is set subjectively. In this context, it is essential to develop and use automated or semi-automated image analysis to produce faster, reproducible, and unbiased data. In this context, we developped ACORBA (Automatic Calculation Of Root Bending Angles), a fully automated software to measure root bending angle over time.

An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. ...

Deep-Learning-for-Medical-Applications is a repository that compiles deep learning methods, code implementations, and examples applied to medical imaging and healthcare data. The project addresses domain-specific challenges like segmentation, classification, detection, and multimodal data (e.g. MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance). It includes Jupyter...