Artificial intelligence as the next step towards precision pathology

B Acs, M Rantalainen, J Hartman - Journal of internal medicine, 2020 - Wiley Online Library
Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic
diagnosis of cancer is increasing as personalized cancer therapy requires accurate …

Breast cancer histopathology image analysis: A review

M Veta, JPW Pluim, PJ Van Diest… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
This paper presents an overview of methods that have been proposed for the analysis of
breast cancer histopathology images. This research area has become particularly relevant …

Impact of deep learning assistance on the histopathologic review of lymph nodes for metastatic breast cancer

DF Steiner, R MacDonald, Y Liu… - The American journal …, 2018 - journals.lww.com
Advances in the quality of whole-slide images have set the stage for the clinical use of digital
images in anatomic pathology. Along with advances in computer image analysis, this raises …

IHC Profiler: an open source plugin for the quantitative evaluation and automated scoring of immunohistochemistry images of human tissue samples

F Varghese, AB Bukhari, R Malhotra, A De - PloS one, 2014 - journals.plos.org
In anatomic pathology, immunohistochemistry (IHC) serves as a diagnostic and prognostic
method for identification of disease markers in tissue samples that directly influences …

Deep convolutional neural networks enable discrimination of heterogeneous digital pathology images

P Khosravi, E Kazemi, M Imielinski, O Elemento… - …, 2018 - thelancet.com
Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and
automated image analysis approaches have great potential to increase precision of …

Determining breast cancer biomarker status and associated morphological features using deep learning

P Gamble, R Jaroensri, H Wang, F Tan… - Communications …, 2021 - nature.com
Background Breast cancer management depends on biomarkers including estrogen
receptor, progesterone receptor, and human epidermal growth factor receptor 2 …

Digital image analysis in breast pathology—from image processing techniques to artificial intelligence

S Robertson, H Azizpour, K Smith, J Hartman - Translational Research, 2018 - Elsevier
Breast cancer is the most common malignant disease in women worldwide. In recent
decades, earlier diagnosis and better adjuvant therapy have substantially improved patient …

Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring

AE Rizzardi, AT Johnson, RI Vogel, SE Pambuccian… - Diagnostic …, 2012 - Springer
Abstract Immunohistochemical (IHC) assays performed on formalin-fixed paraffin-embedded
(FFPE) tissue sections traditionally have been semi-quantified by pathologist visual scoring …

Report on computational assessment of tumor infiltrating lymphocytes from the International Immuno-Oncology Biomarker Working Group

M Amgad, ES Stovgaard, E Balslev, J Thagaard… - NPJ breast …, 2020 - nature.com
Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral
part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer …

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer

ME Vandenberghe, MLJ Scott, PW Scorer… - Scientific reports, 2017 - nature.com
Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for
patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous …