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Digital pathology software#
Digital pathology license#

Overall, GDS provides the following benefits: This direct path increases system bandwidth, decreases latency, and decreases use load on the CPU. GDS enables a direct data path for direct memory access (DMA) transfers between GPU memory and storage, which avoids a bounce buffer through the CPU. Magnum IO GPUDirect Storage (GDS) provides storage I/O acceleration, which is part of the Magnum IO libraries for parallel, asynchronous, and intelligent data center I/O.

Digital pathology license#

The cuCIM library is publicly available under a permissive license (Apache 2.0) and welcomes community contributions.

Use cases include biomedical, geospatial, material and life science, and remote sensing.

Digital pathology software#

cuCIMĬuCIM ( Compute Unified Device Architecture Clara IMage) is an open source, accelerated computer vision and image processing software library for multidimensional images. The use cases featured in this post are benchmarked using the GPU-accelerated tools detailed below. Tools to accelerate WSI I/O and image processing Loading these tiled images from disk into memory and then processing the tiled image can be immensely time-consuming. This forces images to be tiled, meaning that a series of subsamples from the whole slide image are used in modeling. In addition, whole slide images are often very large in size with resolutions higher than 100,000 x 100,000 pixels.

Examples include artifact detection, color normalization, image subsampling, and removal of errant predictions. Whole slide images must be prepared for modeling and the resultant predictions require additional processing for interpretation. Image analysis using deep learning requires substantial preprocessing and postprocessing to improve interpretation and prediction. Incorporating deep learning into processing of whole slide images requires more than simply training and testing a model. Challenges in WSI I/O and image processing Time savings using accelerated histopathology techniques can be critical in the quick identification and treatment of illness and disease.

use GPU-accelerated toolkits to load tiled data from disk directly to GPU memory.

This post explains how GPU-accelerated toolkits improve the input/output (I/O) performance and image processing tasks.

provide new insights about patient data.

apply deep learning to digital images to improve accuracy and reproducibility of clinical analysis.

interpret images using computational approaches.

WSI enables clinicians in histopathology, immunohistochemistry, and cytology to: Whole slide imaging (WSI), the digitization of tissue on slides using whole slide scanners, is gaining traction in healthcare.