Laboratory Computer Performance in a Digital Pathology Environment: Outcomes from a Single Institution

Journal of Pathology Informatics - Tập 9 - Trang 44 - 2018
Mark D. Zarella1, Adam Feldscher2
1Department of Pathology and Laboratory Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
2Department of Computer Science, Drexel University, Philadelphia, PA, USA

Tài liệu tham khảo

Al-Janabi, 2012, Digital pathology: Current status and future perspectives, Histopathology, 61, 1, 10.1111/j.1365-2559.2011.03814.x Zarella, 2018, A practical guide to whole-slide imaging: A white paper from the digital pathology association, Arch Pathol Lab Med Forthcoming Horsman, 2018, I didn’t see that! An examination of internet browser cache behaviour following website visits, Digit Invest, 25, 105, 10.1016/j.diin.2018.02.006 Chen, 2009, Understanding intrinsic characteristics and system implications of flash memory based solid state drives, Sigmetrics Perform Eval Rev, 37, 181, 10.1145/2492101.1555371 Felthousen, 2012, Reducing costs, improving service, and extending the life of computers with solid-state drives, 199 Chen, 2016, Internal parallelism of flash memory-based solid-state drives, ACM Trans Storage, 12, 1, 10.1145/2818376 Bankhead, 2017, QuPath: Open source software for digital pathology image analysis, Sci Rep, 7, 10.1038/s41598-017-17204-5 Kim, 2006, Automated nuclear segmentation in the determination of the Ki-67 labeling index in meningiomas, Clin Neuropathol, 25, 67 Gurcan, 2009, Histopathological image analysis: A review, IEEE Rev Biomed Eng, 2, 147, 10.1109/RBME.2009.2034865 Zarella, 2017, A template matching model for nuclear segmentation in digital images of H&E stained slides Paulik, 2017, An optimized image analysis algorithm for detecting nuclear signals in digital whole slides for histopathology, Cytometry A, 91, 595, 10.1002/cyto.a.23124