output
20192023
most citedDeep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk

49 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

3 papers

physics.med-ph2023★ 7 cited

Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET

Ziping Liu, Joyce C. Mhlanga, Barry A. Siegel +1

Artificial intelligence (AI)-based methods are showing substantial promise in segmenting oncologic positron emission tomography (PET) images. For clinical translation of these meth…

physics.med-ph2021★ 7 cited

Objective task-based evaluation of artificial intelligence-based medical imaging methods: Framework, strategies and role of the physician

Abhinav K. Jha, Kyle J. Myers, Nancy A. Obuchowski +5

Artificial intelligence (AI)-based methods are showing promise in multiple medical-imaging applications. Thus, there is substantial interest in clinical translation of these method…

eess.IV2019★ 49 cited

Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk

Suzanne C Wetstein, Allison M Onken, Christina Luffman +13

Terminal ductal lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cance…