ImageAugmenter：用于医学图像增强的用户友好型 3D 切片工具

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-10-21 DOI:10.1016/j.softx.2024.101923

Ciro Benito Raggio , Paolo Zaffino , Maria Francesca Spadea

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引用次数: 0

摘要

有限的医学图像数据阻碍了生物医学领域深度学习（DL）模型的训练。图像增强可以通过生成现有图像的变体来减少数据稀缺问题。因此，我们推出了 ImageAugmenter，它是 3D Slicer 图像计算平台的一个易于使用的开源模块。它提供了一个简单直观的界面，可同时对医学图像数据集应用 20 多种 MONAI 变换（空间变换、强度变换等），所有这些都无需编程。ImageAugmenter 使医学图像增强成为可能，让更多用户能够通过增加可用于训练的样本数量来提高医学图像分析中 DL 模型的性能。

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ImageAugmenter: A user-friendly 3D Slicer tool for medical image augmentation

Limited medical image data hinders the training of deep learning (DL) models in the biomedical field. Image augmentation can reduce the data-scarcity problem by generating variations of existing images. However, currently implemented methods require coding, excluding non-programmer users from this opportunity.

We therefore present ImageAugmenter, an easy-to-use and open-source module for 3D Slicer imaging computing platform. It offers a simple and intuitive interface for applying over 20 simultaneous MONAI Transforms (spatial, intensity, etc.) to medical image datasets, all without programming.

ImageAugmenter makes accessible medical image augmentation, enabling a wider range of users to improve the performance of DL models in medical image analysis by increasing the number of samples available for training.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.