Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability
This paper introduces the Automated Lesion and Feature Extraction (ALFE) pipeline, an open-source, Python-based pipeline that consumes MR images of the brain and produces anatomical segmentations, lesion segmentations, and human-interpretable imaging features describing the lesions in the brain. ALF...
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| Veröffentlicht in: | Neuroinformatics (Totowa, N.J.) N.J.), 2025-01, Vol.23 (1), p.2, Article 2 |
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| creator | Eghbali, Reza Nedelec, Pierre Weiss, David Bhalerao, Radhika Xie, Long Rudie, Jeffrey D. Liu, Chunlei Sugrue, Leo P. Rauschecker, Andreas M. |
| description | This paper introduces the Automated Lesion and Feature Extraction (ALFE) pipeline, an open-source, Python-based pipeline that consumes MR images of the brain and produces anatomical segmentations, lesion segmentations, and human-interpretable imaging features describing the lesions in the brain. ALFE pipeline is modeled after the neuroradiology workflow and generates features that can be used by physicians for quantitative analysis of clinical brain MRIs and for machine learning applications. The pipeline uses a decoupled design which allows the user to customize the image processing, image registrations, and AI segmentation tools without the need to change the business logic of the pipeline. In this manuscript, we give an overview of ALFE, present the main aspects of ALFE pipeline design philosophy, and present case studies. |
| doi_str_mv | 10.1007/s12021-024-09708-z |
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ALFE pipeline is modeled after the neuroradiology workflow and generates features that can be used by physicians for quantitative analysis of clinical brain MRIs and for machine learning applications. The pipeline uses a decoupled design which allows the user to customize the image processing, image registrations, and AI segmentation tools without the need to change the business logic of the pipeline. 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| subjects | Algorithms Automation Bioinformatics Biomedical and Life Sciences Biomedicine Brain - diagnostic imaging Brain cancer Brain research Computational Biology/Bioinformatics Computer Appl. in Life Sciences Glioma Humans Image Interpretation, Computer-Assisted - methods Image processing Image Processing, Computer-Assisted - methods Lesions Lymphoma Machine Learning Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Neuroimaging Neuroimaging - methods Neurology Neurosciences Open source software Radiomics Software Tumors |
| title | Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability |
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