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Report on computational assessment of tumor infiltrating lymphocytes from the International Immuno-Oncology Biomarker Working Group
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 …
PanCancer insights from The Cancer Genome Atlas: the pathologist's perspective
Abstract The Cancer Genome Atlas (TCGA) represents one of several international consortia
dedicated to performing comprehensive genomic and epigenomic analyses of selected …
dedicated to performing comprehensive genomic and epigenomic analyses of selected …
Predicting cancer outcomes from histology and genomics using convolutional networks
Cancer histology reflects underlying molecular processes and disease progression and
contains rich phenotypic information that is predictive of patient outcomes. In this study, we …
contains rich phenotypic information that is predictive of patient outcomes. In this study, we …
[HTML][HTML] Artificial intelligence and digital microscopy applications in diagnostic hematopathology
Digital Pathology is the process of converting histology glass slides to digital images using
sophisticated computerized technology to facilitate acquisition, evaluation, storage, and …
sophisticated computerized technology to facilitate acquisition, evaluation, storage, and …
The pathologist 2.0: an update on digital pathology in veterinary medicine
CA Bertram, R Klopfleisch - Veterinary pathology, 2017 - journals.sagepub.com
Using light microscopy to describe the microarchitecture of normal and diseased tissues has
changed very little since the middle of the 19th century. While the premise of histologic …
changed very little since the middle of the 19th century. While the premise of histologic …
Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region
Manual count of mitotic figures, which is determined in the tumor region with the highest
mitotic activity, is a key parameter of most tumor grading schemes. It can be, however …
mitotic activity, is a key parameter of most tumor grading schemes. It can be, however …
Automated diagnosis of lymphoma with digital pathology images using deep learning
H El Achi, T Belousova, L Chen, A Wahed… - Annals of Clinical & …, 2019 - annclinlabsci.org
Recent studies have shown promising results in using Deep Learning to detect malignancy
in whole slide imaging, however, they were limited to just predicting a positive or negative …
in whole slide imaging, however, they were limited to just predicting a positive or negative …
Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images
In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to
diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a …
diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a …
An image analysis resource for cancer research: PIIP—Pathology image informatics platform for visualization, analysis, and management
Abstract Pathology Image Informatics Platform (PIIP) is an NCI/NIH sponsored project
intended for managing, annotating, sharing, and quantitatively analyzing digital pathology …
intended for managing, annotating, sharing, and quantitatively analyzing digital pathology …
What can machine vision do for lymphatic histopathology image analysis: a comprehensive review
Over the past 10 years, machine vision (MV) algorithms for image analysis have been
develo** rapidly with computing power. At the same time, histopathological slices can be …
develo** rapidly with computing power. At the same time, histopathological slices can be …