Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data
Analysing brain lesions of various aetiologies necessitates imaging data with subsequent diagnostic techniques that may enable concomitant visualization of spatial anatomical entities, and aberrant molecular behaviour. To fulfil this necessity, several image types and modalities should be collected....
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925000204 |
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| author | Sura Riyadh Saleh Suhad A. Yousif Israa Qader Ahmed |
| author_facet | Sura Riyadh Saleh Suhad A. Yousif Israa Qader Ahmed |
| author_sort | Sura Riyadh Saleh |
| collection | DOAJ |
| description | Analysing brain lesions of various aetiologies necessitates imaging data with subsequent diagnostic techniques that may enable concomitant visualization of spatial anatomical entities, and aberrant molecular behaviour. To fulfil this necessity, several image types and modalities should be collected. This dataset includes MRI (Magnetic Resonance Imaging) with three modalities T2-FLAIR, T1-weighted pre- and post-contrast along with Magnetic Resonance Spectroscopy (MRS) scans for 55 patients. All patients were diagnosed with neoplastic and non-neoplastic brain lesions. T2-FLAIR and contrast-enhanced T1 MRI modalities reveal structural differences in lesions, whereas MRS affords metabolite information. In addition to the imaging data, patient metadata such as age, gender, and expert diagnosis- classify brain lesions into two types: neoplastic (low or high grade) and non-neoplastic. The data were collected between 2023 and 2024 at Al-Andalus Oncology Centre in Baghdad, Iraq, and are publicly available. This dataset is essential as it combines conventional (MRI) and metabolic (MRS) imaging with expert diagnosis information. This dataset is significant as it includes MRI and MRS images along with expert diagnoses information, offering high reuse potential in medical imaging and diagnostic research. |
| format | Article |
| id | doaj-art-dded4e870b62429ca8c946b14494d093 |
| institution | Kabale University |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-dded4e870b62429ca8c946b14494d0932025-01-26T05:04:03ZengElsevierData in Brief2352-34092025-04-0159111288Brain lesion MRI and co-related MRS spectroscopy datasetMendeley DataSura Riyadh Saleh0Suhad A. Yousif1Israa Qader Ahmed2Informatics Institute for Postgraduate Studies, Iraqi Commission for Computers and Informatics, Baghdad, IraqDepartment of Computer Science, College of Science, Al-Nahrain University, Baghdad, IraqDepartment of Neuroradiology, Neurosurgical Hospital, Baghdad, Iraq; Corresponding author.Analysing brain lesions of various aetiologies necessitates imaging data with subsequent diagnostic techniques that may enable concomitant visualization of spatial anatomical entities, and aberrant molecular behaviour. To fulfil this necessity, several image types and modalities should be collected. This dataset includes MRI (Magnetic Resonance Imaging) with three modalities T2-FLAIR, T1-weighted pre- and post-contrast along with Magnetic Resonance Spectroscopy (MRS) scans for 55 patients. All patients were diagnosed with neoplastic and non-neoplastic brain lesions. T2-FLAIR and contrast-enhanced T1 MRI modalities reveal structural differences in lesions, whereas MRS affords metabolite information. In addition to the imaging data, patient metadata such as age, gender, and expert diagnosis- classify brain lesions into two types: neoplastic (low or high grade) and non-neoplastic. The data were collected between 2023 and 2024 at Al-Andalus Oncology Centre in Baghdad, Iraq, and are publicly available. This dataset is essential as it combines conventional (MRI) and metabolic (MRS) imaging with expert diagnosis information. This dataset is significant as it includes MRI and MRS images along with expert diagnoses information, offering high reuse potential in medical imaging and diagnostic research.http://www.sciencedirect.com/science/article/pii/S2352340925000204Brain tumourMRST2-FLAIRT1 and post-contrast T1 |
| spellingShingle | Sura Riyadh Saleh Suhad A. Yousif Israa Qader Ahmed Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data Data in Brief Brain tumour MRS T2-FLAIR T1 and post-contrast T1 |
| title | Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data |
| title_full | Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data |
| title_fullStr | Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data |
| title_full_unstemmed | Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data |
| title_short | Brain lesion MRI and co-related MRS spectroscopy datasetMendeley Data |
| title_sort | brain lesion mri and co related mrs spectroscopy datasetmendeley data |
| topic | Brain tumour MRS T2-FLAIR T1 and post-contrast T1 |
| url | http://www.sciencedirect.com/science/article/pii/S2352340925000204 |
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