Artificial intelligence as the next step towards precision pathology
Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic
diagnosis of cancer is increasing as personalized cancer therapy requires accurate …
diagnosis of cancer is increasing as personalized cancer therapy requires accurate …
Breast cancer histopathology image analysis: A review
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 …
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 …
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 …
method for identification of disease markers in tissue samples that directly influences …
Deep convolutional neural networks enable discrimination of heterogeneous digital pathology images
Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and
automated image analysis approaches have great potential to increase precision of …
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 …
receptor, progesterone receptor, and human epidermal growth factor receptor 2 …
Digital image analysis in breast pathology—from image processing techniques to artificial intelligence
Breast cancer is the most common malignant disease in women worldwide. In recent
decades, earlier diagnosis and better adjuvant therapy have substantially improved patient …
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 …
(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 …
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 …
patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous …