Development and Implementation of an Innovative Framework for Automated Radiomics Analysis in Neuroimaging.
Chiara CamastraGiovanni PasiniAlessandro StefanoGiorgio RussoBasilio VescioFabiano BiniFranco MarinozziAntonio AugimeriPublished in: Journal of imaging (2024)
Radiomics represents an innovative approach to medical image analysis, enabling comprehensive quantitative evaluation of radiological images through advanced image processing and Machine or Deep Learning algorithms. This technique uncovers intricate data patterns beyond human visual detection. Traditionally, executing a radiomic pipeline involves multiple standardized phases across several software platforms. This could represent a limit that was overcome thanks to the development of the matRadiomics application. MatRadiomics, a freely available, IBSI-compliant tool, features its intuitive Graphical User Interface (GUI), facilitating the entire radiomics workflow from DICOM image importation to segmentation, feature selection and extraction, and Machine Learning model construction. In this project, an extension of matRadiomics was developed to support the importation of brain MRI images and segmentations in NIfTI format, thus extending its applicability to neuroimaging. This enhancement allows for the seamless execution of radiomic pipelines within matRadiomics, offering substantial advantages to the realm of neuroimaging.
Keyphrases
- deep learning
- machine learning
- convolutional neural network
- contrast enhanced
- artificial intelligence
- lymph node metastasis
- big data
- healthcare
- quality improvement
- magnetic resonance imaging
- endothelial cells
- electronic health record
- primary care
- high resolution
- squamous cell carcinoma
- mass spectrometry
- diffusion weighted imaging
- multiple sclerosis
- subarachnoid hemorrhage
- functional connectivity
- label free
- optical coherence tomography
- cerebral ischemia
- pluripotent stem cells