NCIP created in 2013 as a part of CBIIT.
Imaging Informatics Working Group created across NCI. Explore needs for research in in vivo, pathology, and omics. Radio-patho genomics for omics.
Need to generate proper therapy for a patient. Look at in vivo imaging, radiology and pathology, run a gene panel to look for abnormal. Look at co-clinical trials (model of a tumor in a mouse that is similar to a human. Experiment therapies on mice.) Run an integrative query to develop a sophisticated diagnosis. Search big data.
Informatics have to let us communicate. Need to be able to compare the data between the omics.
Visual pathology integrative queries–Ashish at Emory. Imaging consistent with ground truth.
Three pilot challenges–pathology, radiology, co-clinical.
Medical Image Computational and computer-assisted Intervention: MICCAI
Interventions in tumors, cardiology, etc that are image-based
Mass General will guide the pilots
Ground truth: find the compatibility of the informatics that we need to run pilots. Take images out of TCIA, CGA, clinical data and compare them.
Put together a primer, examples of data, use cases, how to carry out an integrative query, so that it is understandable.
Jasharee doing MICCAI Challenge in Munich. Segmentation of nuclear imaging in pathology. Combined radiology and pathology classification.
Want to be able to say that these informatics allow us to compare the pathology, rad, co-clinical findings.
Document the approach, technology, application to do a MICCAI challenge the way Jaysharee does it. See their order of march.
Ashish has the conceptual approach for an integrative query system. Learn his order of march.
Need to explain how the challenge management system and integrative query system play together in a scientific scenario.
three tocs: one for challenge steps, one for int query sys. how well does it integrate; what are the common–how do we annotate the tumor in MedICI such that it is compatible with the annotations in the components of the integrative query system. What relationships can we find in the informatics in the animal and patient findings.
How do we better treat our patients?
Describe each section separately and then see if we can merge the two to answer the scientific question.
Challenge Management System, MedICI
Jaysharee's program: Medical Imaging Challenge Infrastructure: MedICI
- Based on open-source CodaLab
- ePAD (created by Daniel Rubin's group at Stanford): tool for annotating images, creates AIM images
- caMicroscope
http://miccai.cloudapp.net:8000/competitions/28
- Competition #1: MICCAI challenge has a training phase where they train their algorithms. A test phase where they run their algorithms on images they have never seen before. They are compared to the ground truth that is determined beforehand. caMicroscope is used to see what is there before and to visualize the results. Overlap/completeness match determines the winner.
- Competition #2: They are given slides.
From PPT: Use titles of slides
Setting up a competition by an organizer. Organizer creates competition bundle.
Can go to cancerimagingarchive.net and create shared lists. Shared lists are pulled into CodaLab. That is how they get the test and training data.
Next is to create ground truth.
Regions of interest in a tumor for annotations are necrosis, adema, and active cancer. Radiologists create the ground truth.
Once participants upload their results, they can see them in ePad.
Integrative Query System
What the data is used for
Relate data from TCIA, caMicroscope, animal model
genomics, animal
how do we make a decision on a firm diagnosis?
