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It has been compared with standard adjuvant therapy with the\u00a0aim of improving prognosis and surgical outcome. Moreover, the response of the tumor to the therapy provides useful information for patient management. The pathological examination of the tissue sections after surgery is the gold\u2010standard to estimate the residual tumor and the assessment of cellularity is an important component of tumor burden assessment. In the current clinical practice, tumor cellularity is manually estimated by pathologists on hematoxylin and eosin (H&amp;E) stained slides, the quality, and reliability of which might be impaired by inter\u2010observer variability which potentially affects prognostic power assessment in NAT trials. This procedure is also qualitative and time\u2010consuming. In this paper, we describe a method of automatically assessing cellularity. A pipeline to automatically segment nuclei figures and estimate residual cancer cellularity from within patches and whole slide images (WSIs) of BCa was developed. We have compared the performance of our proposed pipeline in estimating residual cancer cellularity with that of two expert pathologists. We found an intra\u2010class agreement coefficient (ICC) of 0.89 (95% CI of [0.70, 0.95]) between pathologists, 0.74 (95% CI of [0.70, 0.77]) between pathologist #1 and proposed method, and 0.75 (95% CI of [0.71, 0.79]) between pathologist #2 and proposed method. We have also successfully applied our proposed technique on a WSI to locate areas with high concentration of residual cancer. The main advantage of our approach is that it is fully automatic and can be used to find areas with high cellularity in WSIs. This provides a first step in developing an automatic technique for post\u2010NAT tumor response assessment from pathology slides. \u00a9 2017 International Society for Advancement of Cytometry<\/jats:p>","DOI":"10.1002\/cyto.a.23244","type":"journal-article","created":{"date-parts":[[2017,10,4]],"date-time":"2017-10-04T15:48:36Z","timestamp":1507132116000},"page":"1078-1087","source":"Crossref","is-referenced-by-count":42,"title":["Automatic cellularity assessment from post\u2010treated breast surgical specimens"],"prefix":"10.1002","volume":"91","author":[{"given":"Mohammad","family":"Peikari","sequence":"first","affiliation":[{"name":"Medical Biophysics University of Toronto  Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sherine","family":"Salama","sequence":"additional","affiliation":[{"name":"Laboratory Medicine and Pathobiology University of Toronto  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