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 →
Tidbits from along the way