Automating H&E image-based detection and prognostic evaluation of breast cancers hold promise.
Authors: Satabhisa Mukhopadhyay
Medical Laboratory Observer https://www.mlo-online.com/disease/cancer/article/53071444/advances- in-digital-pathology
This is an invited peer-reviewed by-lined scientific review article (published online on September 21, 23 and in the hardcopy on October 2, 23)
Automated Robust Image Analysis Qualifying H&E Staining Adequacy with Varying Hematoxylin and Eosin Incubation Times.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Christopher Higgins, Alec DeGrand, Lisa M. Williams, Nicolas M. Orsi, Judy Lapetino, Erico von Bueren, Sakura Finetek
2023 NSH Convention
Automated, Ancillary Test-Free BRAF/NRAS Mutational Status Prediction from Digitized Whole Slide Images of H&E-Stained Malignant Melanomas.
Authors: Satabhisa Mukhopadhyay, Angelene Berwick, Elizabeth Walsh, Tathagata Dasgupta, Nick Bennett, Nicolas M. Orsi
USCAP 2023
Targeting the Forgotten How to empower patients in histopathology diagnostics as we navigate the emergent digital era.
Authors: Angelene Berwick, Graham Holland, Bradford Power, Nicolas M. Orsi
Prediction of disease recurrence in low risk Oncotype Dx breast cancers from digital H&E-stained whole slide images of pre-treatment resections alone.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Elizabeth Walsh, Rebecca Millican-Slater, Andrew Hanby, Joanne Stephenson, Craig A. Bunnell, Nicolas M. Orsi
Attrition Rate and Case Completeness for Identifying Invasive Breast Carcinoma from Digitized Whole Slide Images in a Real-World Setting.
Authors: Nicolas Orsi, Satabhisa Mukhopadhyay, Tathagata Dasgupta, Elizabeth Walsh, Angelene Berwick, Matthew Hanna, Rajendra Singh
DPA Pathology Vision 2022
Automated H&E whole slide image surrogate Ki67 index prediction and prognostic value across breast cancer subtypes.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Angelene Berwick, Elizabeth Walsh, Andrew Hanby, Rebecca Millican-Slater, Michele Cummings, Nicolas M. Orsi
Automated H&E image-based detection and prognostic evaluation of HER2 heterogeneity in ER+ breast cancers.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Angelene Berwick, Elizabeth Walsh, Michele Cummings, Nicolas M. Orsi
One Step Beyond: Artificial Intelligence for Image-Based Prognostication Leveraging artificial intelligence for tumor detection and prognostication.
Authors: Nicolas M. Orsi, Elizabeth Walsh, Katie Allen
Extracting the Right Data for Patient Care.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta
A novel, computer-aided, scanning platform agnostic solution for grading carcinomas in breast biopsy whole slide images.
Authors: Nicolas M. Orsi, Tathagata Dasgupta, Satabhisa Mukhopadhyay, Michele Cummings, Angelene Berwick
Automated immunostaining-free prediction of breast carcinoma ER and PR status, Ki67 count, patient therapy stratification index and quantification of prognostic quiescence burden in TNBC from pretreatment H&E stained histopathology images in breast cancer.heterogeneity profiling in breast cancer.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Nicolas M. Orsi, Michele Cummings, Angelene Berwick
Automated, IHC/FISH-free, H&E histopathology image-based HER2 amplification, tumor infiltrating lymphocyte (TIL) and tumor heterogeneity profiling in breast cancer.
Authors: Satabhisa Mukhopadhyay, Tathagata Dasgupta, Nicolas M. Orsi, Michele Cummings, Angelene Berwick