DeepAI AI Chat
Log In Sign Up

FastPathology: An open-source platform for deep learning-based research and decision support in digital pathology

by   André Pedersen, et al.

Deep convolutional neural networks (CNNs) are the current state-of-the-art for digital analysis of histopathological images. The large size of whole-slide microscopy images (WSIs) requires advanced memory handling to read, display and process these images. There are several open-source platforms for working with WSIs, but few support deployment of CNN models. These applications use third-party solutions for inference, making them less user-friendly and unsuitable for high-performance image analysis. To make deployment of CNNs user-friendly and feasible on low-end machines, we have developed a new platform, FastPathology, using the FAST framework and C++. It minimizes memory usage for reading and processing WSIs, deployment of CNN models, and real-time interactive visualization of results. Runtime experiments were conducted on four different use cases, using different architectures, inference engines, hardware configurations and operating systems. Memory usage for reading, visualizing, zooming and panning a WSI were measured, using FastPathology and three existing platforms. FastPathology performed similarly in terms of memory to the other C++ based application, while using considerably less than the two Java-based platforms. The choice of neural network model, inference engine, hardware and processors influenced runtime considerably. Thus, FastPathology includes all steps needed for efficient visualization and processing of WSIs in a single application, including inference of CNNs with real-time display of the results. Source code, binary releases and test data can be found online on GitHub at


page 1

page 3

page 4

page 5

page 6


AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing

The advancement of Deep Learning (DL) is driven by efficient Deep Neural...

daBNN: A Super Fast Inference Framework for Binary Neural Networks on ARM devices

It is always well believed that Binary Neural Networks (BNNs) could dras...

Real-Time Super-Resolution System of 4K-Video Based on Deep Learning

Video super-resolution (VSR) technology excels in reconstructing low-qua...

Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization

Deep learning methods have emerged as powerful tools for analyzing histo...

Making Convolutions Resilient via Algorithm-Based Error Detection Techniques

The ability of Convolutional Neural Networks (CNNs) to accurately proces...

Code Repositories


⚡ Open-source software for deep learning-based digital pathology

view repo