Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma.
Saima RathoreSpyridon BakasSarthak PatiHamed AkbariRatheesh KalarotPatmaa SridharanMartin RozyckiMark BergmanBirkan TuncRagini VermaMichel BilelloChristos DavatzikosPublished in: Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries. BrainLes (Workshop) (2018)
Quantitative research, especially in the field of radio(geno)mics, has helped us understand fundamental mechanisms of neurologic diseases. Such research is integrally based on advanced algorithms to derive extensive radiomic features and integrate them into diagnostic and predictive models. To exploit the benefit of such complex algorithms, their swift translation into clinical practice is required, currently hindered by their complicated nature. brain-CaPTk is a modular platform, with components spanning across image processing, segmentation, feature extraction, and machine learning, that facilitates such translation, enabling quantitative analyses without requiring substantial computational background. Thus, brain-CaPTk can be seamlessly integrated into the typical quantification, analysis and reporting workflow of a radiologist, underscoring its clinical potential. This paper describes currently available components of brain-CaPTk and example results from their application in glioblastoma.
Keyphrases
- machine learning
- white matter
- deep learning
- resting state
- high resolution
- clinical practice
- cerebral ischemia
- squamous cell carcinoma
- artificial intelligence
- high throughput
- big data
- multiple sclerosis
- convolutional neural network
- risk assessment
- photodynamic therapy
- electronic health record
- subarachnoid hemorrhage