Digital pathology image analysis: opportunities and challenges - PubMed (original) (raw)
- PMID: 30147749
- PMCID: PMC6107089
- DOI: 10.2217/IIM.09.9
Digital pathology image analysis: opportunities and challenges
Anant Madabhushi. Imaging Med. 2009.
No abstract available
Similar articles
- Image analysis and machine learning in digital pathology: Challenges and opportunities.
Madabhushi A, Lee G. Madabhushi A, et al. Med Image Anal. 2016 Oct;33:170-175. doi: 10.1016/j.media.2016.06.037. Epub 2016 Jul 4. Med Image Anal. 2016. PMID: 27423409 Free PMC article. Review. - Digital pathology: Review of current opportunities and challenges for oral pathologists.
Liu Y, Pantanowitz L. Liu Y, et al. J Oral Pathol Med. 2019 Apr;48(4):263-269. doi: 10.1111/jop.12825. Epub 2019 Feb 8. J Oral Pathol Med. 2019. PMID: 30618114 Review. - [Digital pathology in immuno-oncology-current opportunities and challenges : Overview of the analysis of immune cell infiltrates using whole slide imaging].
Grabe N, Roth W, Foersch S. Grabe N, et al. Pathologe. 2018 Nov;39(6):539-545. doi: 10.1007/s00292-018-0540-9. Pathologe. 2018. PMID: 30350177 Review. German. - Commentary: Roles for Pathologists in a High-throughput Image Analysis Team.
Aeffner F, Wilson K, Bolon B, Kanaly S, Mahrt CR, Rudmann D, Charles E, Young GD. Aeffner F, et al. Toxicol Pathol. 2016 Aug;44(6):825-34. doi: 10.1177/0192623316653492. Epub 2016 Jun 24. Toxicol Pathol. 2016. PMID: 27343178 - Semantic Integrative Digital Pathology: Insights into Microsemiological Semantics and Image Analysis Scalability.
Racoceanu D, Capron F. Racoceanu D, et al. Pathobiology. 2016;83(2-3):148-55. doi: 10.1159/000443964. Epub 2016 Apr 26. Pathobiology. 2016. PMID: 27100713
Cited by
- Quantitative Histomorphometric Features of Prostate Cancer Predict Patients Who Biochemically Recur Following Prostatectomy.
Duenweg SR, Brehler M, Lowman AK, Bobholz SA, Kyereme F, Winiarz A, Nath B, Iczkowski KA, Jacobsohn KM, LaViolette PS. Duenweg SR, et al. Lab Invest. 2023 Dec;103(12):100269. doi: 10.1016/j.labinv.2023.100269. Epub 2023 Oct 26. Lab Invest. 2023. PMID: 37898290 Free PMC article. - Development and validation of a multivariable model for prediction of malignant transformation and recurrence of oral epithelial dysplasia.
Mahmood H, Shephard A, Hankinson P, Bradburn M, Araujo ALD, Santos-Silva AR, Lopes MA, Vargas PA, McCombe KD, Craig SG, James J, Brooks J, Nankivell P, Mehanna H, Rajpoot N, Khurram SA. Mahmood H, et al. Br J Cancer. 2023 Nov;129(10):1599-1607. doi: 10.1038/s41416-023-02438-0. Epub 2023 Sep 27. Br J Cancer. 2023. PMID: 37758836 Free PMC article. - Whole slide imaging (WSI) scanner differences influence optical and computed properties of digitized prostate cancer histology.
Duenweg SR, Bobholz SA, Lowman AK, Stebbins MA, Winiarz A, Nath B, Kyereme F, Iczkowski KA, LaViolette PS. Duenweg SR, et al. J Pathol Inform. 2023 Jul 4;14:100321. doi: 10.1016/j.jpi.2023.100321. eCollection 2023. J Pathol Inform. 2023. PMID: 37496560 Free PMC article. - NRK-ABMIL: Subtle Metastatic Deposits Detection for Predicting Lymph Node Metastasis in Breast Cancer Whole-Slide Images.
Sajjad U, Rezapour M, Su Z, Tozbikian GH, Gurcan MN, Niazi MKK. Sajjad U, et al. Cancers (Basel). 2023 Jun 30;15(13):3428. doi: 10.3390/cancers15133428. Cancers (Basel). 2023. PMID: 37444538 Free PMC article. - Comparison of a machine and deep learning model for automated tumor annotation on digitized whole slide prostate cancer histology.
Duenweg SR, Brehler M, Bobholz SA, Lowman AK, Winiarz A, Kyereme F, Nencka A, Iczkowski KA, LaViolette PS. Duenweg SR, et al. PLoS One. 2023 Mar 16;18(3):e0278084. doi: 10.1371/journal.pone.0278084. eCollection 2023. PLoS One. 2023. PMID: 36928230 Free PMC article.
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.
LinkOut - more resources
Full Text Sources
Other Literature Sources