Prostate biopsy whole slide image dataset from an underrepresented Middle Eastern population
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912746479550464 |
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| author | Ali, Peshawa J. Muhammad Vincent, Navin Abdulla, Saman S. Fadhl, Han N. Mohammed Blilie, Anders Szolnoky, Kelvin Mielcarz, Julia Anna Ji, Xiaoyi Kartasalo, Kimmo Al-Talabani, Abdulbasit K. Mulliqi, Nita |
| author_facet | Ali, Peshawa J. Muhammad Vincent, Navin Abdulla, Saman S. Fadhl, Han N. Mohammed Blilie, Anders Szolnoky, Kelvin Mielcarz, Julia Anna Ji, Xiaoyi Kartasalo, Kimmo Al-Talabani, Abdulbasit K. Mulliqi, Nita |
| contents | Artificial intelligence (AI) is increasingly used in digital pathology. Publicly available histopathology datasets remain scarce, and those that do exist predominantly represent Western populations. Consequently, the generalizability of AI models to populations from less digitized regions, such as the Middle East, is largely unknown. This motivates the public release of our dataset to support the development and validation of pathology AI models across globally diverse populations. We present 339 whole-slide images of prostate core needle biopsies from a consecutive series of 185 patients collected in Erbil, Iraq. The slides are associated with Gleason scores and International Society of Urological Pathology grades assigned independently by three pathologists. Scanning was performed using two high-throughput scanners (Leica and Hamamatsu) and one compact scanner (Grundium). All slides were de-identified and are provided in their native formats without further conversion. The dataset enables grading concordance analyses, color normalization, and cross-scanner robustness evaluations. Data will be deposited in the Bioimage Archive (BIA) under accession code: to be announced (TBA), and released under a CC BY 4.0 license. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_03854 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Prostate biopsy whole slide image dataset from an underrepresented Middle Eastern population Ali, Peshawa J. Muhammad Vincent, Navin Abdulla, Saman S. Fadhl, Han N. Mohammed Blilie, Anders Szolnoky, Kelvin Mielcarz, Julia Anna Ji, Xiaoyi Kartasalo, Kimmo Al-Talabani, Abdulbasit K. Mulliqi, Nita Computer Vision and Pattern Recognition Artificial intelligence (AI) is increasingly used in digital pathology. Publicly available histopathology datasets remain scarce, and those that do exist predominantly represent Western populations. Consequently, the generalizability of AI models to populations from less digitized regions, such as the Middle East, is largely unknown. This motivates the public release of our dataset to support the development and validation of pathology AI models across globally diverse populations. We present 339 whole-slide images of prostate core needle biopsies from a consecutive series of 185 patients collected in Erbil, Iraq. The slides are associated with Gleason scores and International Society of Urological Pathology grades assigned independently by three pathologists. Scanning was performed using two high-throughput scanners (Leica and Hamamatsu) and one compact scanner (Grundium). All slides were de-identified and are provided in their native formats without further conversion. The dataset enables grading concordance analyses, color normalization, and cross-scanner robustness evaluations. Data will be deposited in the Bioimage Archive (BIA) under accession code: to be announced (TBA), and released under a CC BY 4.0 license. |
| title | Prostate biopsy whole slide image dataset from an underrepresented Middle Eastern population |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2512.03854 |