Research graph
References from Comparison and image analysis of different file formats on whole-slide images for colorectal and non-small cell lung carcinomas. Local targets link to admitted publications; unresolved targets remain external evidence.
Basic concepts in digitizing slides: an overview
10.21608/aced.2023.244791.1023 · 2023 · External reference
Whole slide imaging in pathology: advantages, limitations, and emerging perspectives
2015 · External reference
Whole-slide image focus quality: automatic assessment and impact on AI cancer detection
10.4103/jpi.jpi_11_19 · 2019 · External reference
Impact of altering various image parameters on human epidermal growth factor receptor 2 image analysis data quality
10.4103/jpi.jpi_46_17 · 2017 · External reference
Whole slide imaging (WSI) scanner differences influence optical and computed properties of digitized prostate cancer histology
10.1016/j.jpi.2023.100321 · 2023 · External reference
Developing image analysis methods for digital pathology
10.1002/path.5921 · 2022 · External reference
Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice
10.1038/s41379-021-01000-8 · 2022 · External reference
Implementing the DICOM standard for digital pathology
10.4103/jpi.jpi_42_18 · 2018 · External reference
Comparative assessment of digital pathology systems for primary diagnosis
10.4103/jpi.jpi_94_20 · 2021 · External reference
Breaking data silos: incorporating the DICOM imaging standard into the OMOP CDM to enable multimodal research
2025 · External reference
Dual-personality DICOM-TIFF for whole slide images: a migration technique for legacy software
10.4103/jpi.jpi_93_18 · 2019 · External reference
Standardization in digital pathology: supplement 145 of the DICOM standards
10.4103/2153-3539.80719 · 2011 · External reference
Domain-ensemble learning with cross-domain mixup for thoracic disease classification in unseen domains
10.1016/j.bspc.2022.104488 · 2023 · External reference
A closer look at domain shift in deep learning for digital pathology
2019 · External reference
Lossy DICOM conversion may affect AI performance
10.1038/s41598-025-02851-w · 2025 · External reference
Synergies and challenges in the preclinical and clinical implementation of pathology artificial intelligence applications
10.1016/j.mcpdig.2023.08.007 · 2023 · External reference
