Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis

Fuente: arXiv
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Main Authors: Primakov, Sergey, Lavrova, Elizaveta, Salahuddin, Zohaib, Woodruff, Henry C, Lambin, Philippe
Format: Preprint
Published: 2022
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author Primakov, Sergey
Lavrova, Elizaveta
Salahuddin, Zohaib
Woodruff, Henry C
Lambin, Philippe
author_facet Primakov, Sergey
Lavrova, Elizaveta
Salahuddin, Zohaib
Woodruff, Henry C
Lambin, Philippe
contents Medical image analysis plays a key role in precision medicine as it allows the clinicians to identify anatomical abnormalities and it is routinely used in clinical assessment. Data curation and pre-processing of medical images are critical steps in the quantitative medical image analysis that can have a significant impact on the resulting model performance. In this paper, we introduce a precision-medicine-toolbox that allows researchers to perform data curation, image pre-processing and handcrafted radiomics extraction (via Pyradiomics) and feature exploration tasks with Python. With this open-source solution, we aim to address the data preparation and exploration problem, bridge the gap between the currently existing packages, and improve the reproducibility of quantitative medical imaging research.
format Preprint
id arxiv_https___arxiv_org_abs_2202_13965
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis
Primakov, Sergey
Lavrova, Elizaveta
Salahuddin, Zohaib
Woodruff, Henry C
Lambin, Philippe
Image and Video Processing
Computer Vision and Pattern Recognition
Machine Learning
Quantitative Methods
Medical image analysis plays a key role in precision medicine as it allows the clinicians to identify anatomical abnormalities and it is routinely used in clinical assessment. Data curation and pre-processing of medical images are critical steps in the quantitative medical image analysis that can have a significant impact on the resulting model performance. In this paper, we introduce a precision-medicine-toolbox that allows researchers to perform data curation, image pre-processing and handcrafted radiomics extraction (via Pyradiomics) and feature exploration tasks with Python. With this open-source solution, we aim to address the data preparation and exploration problem, bridge the gap between the currently existing packages, and improve the reproducibility of quantitative medical imaging research.
title Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis
topic Image and Video Processing
Computer Vision and Pattern Recognition
Machine Learning
Quantitative Methods
url https://arxiv.org/abs/2202.13965