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RCBio is a HPC pipeline runner and workflow tool supported by HMS RC consultants. It was first designed for a Neubiology lab and later opened to all O2 users. RCBio helps users to quickly build and run multiple steps data analysis pipeline on a computer cluster. RCBio automatically keeps logs on all job status and use email to notify user. When re-run the same pipeline, RCBio automatically submit failed jobs and ask user if she/he want to re-run the successful jobs. Here is our wiki page about the RCBio project: RC workflows

Overview

Medical images are obtained from various sources including MRI, CT, X-ray, ultrasound, and PET scans. Analyzing these images necessitates a comprehensive environment for data access, visualization, processing, and algorithm development. A key challenge involves extracting quantitative features to generate clinically relevant information using advanced techniques like machine learning algorithms.  This presentation will explore radiomics, which captures characteristics not typically visible. Radiomics features can be employed across various medical imaging modalities and applications, enabling the study of associations between imaging features and patient biology, as well as the prediction of clinical outcomes, making radiomics a versatile technique in medical imaging. These features quantify shape, intensity, and texture characteristics within medical images, reducing reliance on subjective interpretation for clinical workflows.

Highlights

In this session, you will learn how to:

• Import and manage large sets of images without loading them into memory,

• Extract shape, intensity, and texture radiomics features,

• Reduce the number of extracted features for classification,  

• Build a deep learning network to classify images, and

• Review and analyze the results.