Precision-medicine-toolbox: An open-source python package for the quantitative medical image analysis

Medical image analysis plays a key role in precision medicine. Data curation and pre-processing are critical steps in quantitative medical image analysis that can have a significant impact on the resulting performance of machine learning models. In this work, we introduce the Precision-medicine-tool...

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Bibliographic Details
Published in:Software impacts Vol. 16; p. 100508
Main Authors: Lavrova, Elizaveta, Primakov, Sergey, Salahuddin, Zohaib, Beuque, Manon, Verstappen, Damon, Woodruff, Henry C., Lambin, Philippe
Format: Journal Article
Language:English
Published: Elsevier B.V 01.05.2023
Subjects:
Computer science
DICOM
Engineering, computing & technology
Features
Image pre-processing
Ingénierie, informatique & technologie
Medical imaging research
Radiomics
Sciences informatiques
Software
Statistical analysis
Medical imaging research
Features
Statistical analysis
DICOM
Image pre-processing
Radiomics
ISSN:2665-9638, 2665-9638
Online Access:Get full text
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Summary:Medical image analysis plays a key role in precision medicine. Data curation and pre-processing are critical steps in quantitative medical image analysis that can have a significant impact on the resulting performance of machine learning models. In this work, we introduce the Precision-medicine-toolbox, allowing clinical and junior researchers to perform data curation, image pre-processing, radiomics extraction, and feature exploration tasks with a customizable Python package. With this open-source tool, we aim to facilitate the crucial data preparation and exploration steps, bridge the gap between the currently existing packages, and improve the reproducibility of quantitative medical imaging research. •Medical imaging demands automation but is lacking methodology standardization.•Medical imaging data curation and exploration are performed in an in-house manner.•Our toolbox is aimed to fill these gaps and enable automated pipelines in radiomics.•The toolbox will increase reproducibility in quantitative medical imaging research.•The community is encouraged to contribute to develop a powerful tool for radiomics.
Bibliography:scopus-id:2-s2.0-85154042329
ISSN:2665-9638
2665-9638
DOI:10.1016/j.simpa.2023.100508