Pediatric brain tumor classification using digital histopathology and deep learning: evaluation of SOTA methods on a multi-center Swedish cohort
机构 * Department of Biomedical Engineering, Linköping University, Sweden(生物医学工程系,利厄普大学) ; Center for Medical Image Science and Visualization, Linköping University, Sweden(医学影像科学与可视化中心,利厄普大学) ; Crown Princess Victoria Children’s Hospital and Department of Health, Medicine and Caring Sciences, Linköping University, Sweden(维多利亚公主儿童医院和健康、医学与关怀科学系,利厄普大学) ; Department of Radiology and Department of Health, Medicine and Caring Sciences, Linköping University, Sweden(放射科和健康、医学与关怀科学系,利厄普大学) ; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden(肿瘤病理学系,卡罗林斯卡研究所,索纳) ; Department of Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital, Sweden(临床病理学和癌症诊断系,卡罗林斯卡大学医院) ; Department of Radiation Physics and Department of Medical and Health Sciences, Linköping University, Sweden(放射物理系和医学与健康科学系,利厄普大学)
专题命中 病理影像 :pathology(abstract,journal_ref);分类 cs.CV
Journal ref Tampu IE et al. Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort. Brain Pathology. 2025. e70029