Digital pathology image analysis: opportunities and challenges
- PMID: 30147749
- PMCID: PMC6107089
- DOI: 10.2217/IIM.09.9
Digital pathology image analysis: opportunities and challenges
References
-
- Allsbrook WC Jr, Mangold KA, Johnson MH, Lane RB, Lane CG, Epstein JI: Interobserver reproducibility of Gleason grading of prostatic carcinoma: general pathologist. Hum. Pathol 32(1), 81–88 (2001). - PubMed
-
- Epstein JI, Allsbrook WC Jr, Amin MB, Egevad LL: Update on the Gleason grading system for prostate cancer: results of an international consensus conference of urologic pathologists. Adv. Anat. Pathol 13(1), 57–59 (2006). - PubMed
-
- Anderson NH, Hamilton PW, Bartels PH, Thompson D, Montironi R, Sloan JM: Computerized scene segmentation for the discrimination of architectural features in ductal proliferative lesions of the breast. J. Pathol 181, 374–380 (1997). - PubMed
-
- Basavanhally A, Agner A, Alexe G, Ganesan S, Bhanot G, Madabhushi A: Manifold learning with graph-based features for identifying extent of lymphocytic infiltration from high grade breast cancer histology. Presented at: MMBIA Workshop in Conjunction with MICCAI 2008 New York, NY, USA, 10 September 2008.
-
- Basavanhally A, Xu J, Ganesan S, Madabhushi A: Computer-aided prognosis (CAP) of ER+ breast cancer histopathology and correlating survival outcome with oncotype Dx assay. Presented at: IEEE International Symposium on Biomedical Imaging (ISBI) Boston, MA, USA, 28 June–1 July 2009.
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources