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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2412.16568 |
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| _version_ | 1866909437833248768 |
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| author | Fernandes, Margarida Soares, José Silva, Matheus Saraiva, Crystian Alves, Victor |
| author_facet | Fernandes, Margarida Soares, José Silva, Matheus Saraiva, Crystian Alves, Victor |
| contents | Brain metastases are a common diagnosis that affects between 20% and 40% of cancer patients. Subsequent to radiation therapy, patients with brain metastases undergo follow-up sessions during which the response to treatment is monitored. In this study, a dataset of medical images from 44 patients with at least one brain metastasis and different primary tumor locations was collected and processed. Each patient was treated with either a linear accelerator or a gamma knife. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans were collected at various time points, including before treatment and during follow-up sessions. The CT datasets were processed using windowing and artifact reduction techniques, while the MRI datasets were subjected to CLAHE. The NifTI files corresponding to the CT and MRI images were made public available. In order to align the datasets of each patient, a multimodal registration was performed between the CT and MRI datasets, with different software options being tested. The fusion matrices were provided together with the dataset. The aforementioned steps resulted in the creation of an optimized dataset, prepared for use in a range of studies related to brain metastases. RFUds is publicity available at zenodo under the DOI 10.5281/zenodo.14524784. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_16568 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RFUDS -- A Brain Metastases Imaging Dataset of Radiotherapy Follow-Up Fernandes, Margarida Soares, José Silva, Matheus Saraiva, Crystian Alves, Victor Image and Video Processing Brain metastases are a common diagnosis that affects between 20% and 40% of cancer patients. Subsequent to radiation therapy, patients with brain metastases undergo follow-up sessions during which the response to treatment is monitored. In this study, a dataset of medical images from 44 patients with at least one brain metastasis and different primary tumor locations was collected and processed. Each patient was treated with either a linear accelerator or a gamma knife. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans were collected at various time points, including before treatment and during follow-up sessions. The CT datasets were processed using windowing and artifact reduction techniques, while the MRI datasets were subjected to CLAHE. The NifTI files corresponding to the CT and MRI images were made public available. In order to align the datasets of each patient, a multimodal registration was performed between the CT and MRI datasets, with different software options being tested. The fusion matrices were provided together with the dataset. The aforementioned steps resulted in the creation of an optimized dataset, prepared for use in a range of studies related to brain metastases. RFUds is publicity available at zenodo under the DOI 10.5281/zenodo.14524784. |
| title | RFUDS -- A Brain Metastases Imaging Dataset of Radiotherapy Follow-Up |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2412.16568 |