• 0 Citations
20192019
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Research Output 2019 2019

  • 2 Conference contribution

Deep learning networks to segment and detect breast terminal duct lobular units, acini, and adipose tissue: a step toward the automated analysis of lobular involution as a marker for breast cancer risk

Onken, A., Wetstein, S., Pyle, M., Pluim, J., Schnitt, S., Baker, G., Collins, L., Tamimi, R., Veta, M. & Heng, Y., 2019, (Accepted/In press) United States and Canadian Academy of Pathology (USCAP).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

Adipose Tissue
Breast
Learning
Breast Neoplasms
Physiological Phenomena

Detection of acini in histopathology slides: towards automated prediction of breast cancer risk

Wetstein, S., Onken, A., Baker, G., Pyle, M., Pluim, J., Tamimi, R., Heng, Y. & Veta, M., 18 Mar 2019, Medical Imaging 2019: Digital Pathology. Tomaszewski, J. E. & Ward, A. D. (eds.). Bellingham, 7 p. 109560Q. (Proceedings of SPIE; vol. 10956)

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Ducts
Labels
Masks
Health
Biomarkers