Tag Archives: deep learning

Use Case 4: Lymphocyte Detection

Typically, you’ll want to use a validation set to determine an optimal threshold as it is often not .5 (which is equivalent to argmax). Subsequently, use this threshold on the the “_prob” image to generate a binary image.This blog posts explains how to train a deep learning lymphocyte detector in accordance with our paper “Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases”.

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Installing Caffe on the Ohio Super Computing (OSC) Ruby Cluster

One of the perks of working at Case Western Reserve is that we often qualify for access to cutting edge resource and special projects. In this case, since our digital histology deep learning work requires a large number of GPUs to analyze thousands of patients, we were granted access to the OSC Ruby cluster, which has 20 NVIDIA Tesla K40 GPUs. Since the cluster has only recently been setup, there was some leg work required on our end to get Caffe  fully up and running, without root access, which we’ll document here.

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