Animation below speaks for itself : )
Finally put together a script which makes jupyter notebooks plots interactive, such that when hovering over a scatter point plot, the underlying image displays, see demo + code below:
Very useful when looking at e.g. embeddings.
If the dataset is too large to store in memory, line 70 can be replaced with a real-time load command
Code is available here: https://github.com/choosehappy/Snippets/blob/master/interactive_image_popup_on_hover.py
Digital pathology image analysis requires high quality input images. While there are a large number of images available in The Cancer Genome Atlas (TCGA), the ones which are currently available in the data portal are frozen specimens and are *not* suitable for computational analysis. This post discusses how to download the Formalin-Fixed Paraffin-Embedded (FFPE) slides for corresponding patients.
Continue reading Download TCGA Digital Pathology Images (FFPE)
This blog post is based on the net surgery example provided by Caffe. It takes the concept and expands it to a working example to produce pixel-wise output images, generating output in ~2 seconds (simple approach) or ~35 seconds (advanced approach) for a 2,000 x 2,000 image, an improvement from the ~15 hours of a naive pixel wise approach.
Continue reading Efficient pixel-wise deep learning on large images