The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity
Abstract
Textural and shape analysis is gaining considerable interest in medical imaging, particularly to identify parameters characterizing tumor heterogeneity and to feed radiomic models. Here, we present a free, multiplatform, and easy-to-use freeware called LIFEx, which enables the calculation of conventional, histogram-based, textural, and shape features from PET, SPECT, MR, CT, and US images, or from any combination of imaging modalities. The application does not require any programming skills and was developed for medical imaging professionals. The goal is that independent and multicenter evidence of the usefulness and limitations of radiomic features for characterization of tumor heterogeneity and subsequent patient management can be gathered. Many options are offered for interactive textural index calculation and for increasing the reproducibility among centers. The software already benefits from a large user community (more than 800 registered users), and interactions within that community are part of the development strategy. Significance: This study presents a user-friendly, multi-platform freeware to extract radiomic features from PET, SPECT, MR, CT, and US images, or any combination of imaging modalities. Cancer Res; 78(16); 4786–9. ©2018 AACR.
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Cites
Radiomics: Images Are More than Pictures, They Are Data
Gillies, R. J., Kinahan, P. E., & Hricak, H. (2016) · Radiology · doi:10.1148/radiol.2015151169 · Cited by 8,421
Cited by
Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics
Orlhac, F., Frouin, F., Nioche, C., Ayache, N., & Buvat, I. (2019) · Radiology · doi:10.1148/radiol.2019182023 · Cited by 411
Self-citationZwanenburg, A. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04391-8 · Cited by 306
Papadimitroulas, P., Brocki, L., Christopher Chung, N., Marchadour, W., Vermet, F., Gaubert, L., Eleftheriadis, V., Plachouris, D., Visvikis, D., Kagadis, G. C., et al. (2021) · Physica Medica · doi:10.1016/j.ejmp.2021.03.009 · Cited by 226
Hyun, S. H., Ahn, M. S., Koh, Y. W., & Lee, S. J. (2019) · Clinical Nuclear Medicine · doi:10.1097/rlu.0000000000002810 · Cited by 185
Tricarico, P., Chardin, D., Martin, N., Contu, S., Hugonnet, F., Otto, J., & Humbert, O. (2024) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2023-007628 · Cited by 38
Metadata
- Authors
- Nioche, C., Orlhac, F., Boughdad, S., Reuzé, S., Goya-Outi, J., Robert, C., Pellot-Barakat, C., Soussan, M., Frouin, F., & Buvat, I.
- Venue
- Cancer Research
- Published
- 2018-08-14
- Volume
- 78
- Issue
- 16
- Pages
- 4786-4789
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- OpenAlex
- W2809848353
- Cited by
- 1,167
- References
- 1
- FWCI
- 59.22
- Type
- journal article
- Language
- en
- Open access
- closed
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- Nioche, C., Orlhac, F., Boughdad, S., Reuzé, S., Goya-Outi, J., Robert, C., Pellot-Barakat, C., Soussan, M., Frouin, F., & Buvat, I. (2018). LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity. Cancer Research. https://doi.org/10.1158/0008-5472.can-18-0125
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