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View article: Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon
Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon Open
The National Cancer Institute (NCI) supports numerous research consortia that rely on imaging technologies to study cancerous tissues. To foster collaboration and innovation in this field, the Image Analysis Working Group (IAWG) was create…
View article: Suppression of dystroglycan function accompanies pancreatic acinar‐to‐ductal metaplasia and favours dysplasia development
Suppression of dystroglycan function accompanies pancreatic acinar‐to‐ductal metaplasia and favours dysplasia development Open
The basement membrane (BM) is among the predominant microenvironmental factors of normal epithelia and of precancerous epithelial lesions. Evidence suggests that the BM functions not only as a barrier to tumour invasion but also as an acti…
View article: 3D multiplexed tissue imaging reconstruction and optimized region of interest (ROI) selection through deep learning model of channels embedding
3D multiplexed tissue imaging reconstruction and optimized region of interest (ROI) selection through deep learning model of channels embedding Open
Introduction: Tissue-based sampling and diagnosis are defined as the extraction of information from certain limited spaces and its diagnostic significance of a certain object. Pathologists deal with issues related to tumor heterogeneity si…
View article: Addressing persistent challenges in digital image analysis of cancerous tissues
Addressing persistent challenges in digital image analysis of cancerous tissues Open
The National Cancer Institute (NCI) supports many research programs and consortia, many of which use imaging as a major modality for characterizing cancerous tissue. A trans-consortia Image Analysis Working Group (IAWG) was established in …
View article: 3D multiplexed tissue imaging reconstruction and optimized region-of-interest (ROI) selection through deep learning model of channels embedding
3D multiplexed tissue imaging reconstruction and optimized region-of-interest (ROI) selection through deep learning model of channels embedding Open
Tissue-based sampling and diagnosis are defined as the extraction of information from certain limited spaces and its diagnostic significance of a certain object. Pathologists deal with issues related to tumor heterogeneity since analyzing …
View article: A Novel Mouse Model that Recapitulates the Heterogeneity of Human Triple Negative Breast Cancer
A Novel Mouse Model that Recapitulates the Heterogeneity of Human Triple Negative Breast Cancer Open
Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new targeted therapies, but few TNBC mouse models exist. Here, we developed a novel TNBC m…
View article: Computational multiplex panel reduction to maximize information retention in breast cancer tissue microarrays
Computational multiplex panel reduction to maximize information retention in breast cancer tissue microarrays Open
Recent state-of-the-art multiplex imaging techniques have expanded the depth of information that can be captured within a single tissue sample by allowing for panels with dozens of markers. Despite this increase in capacity, space on the p…
View article: Computational Multiplex Panel Reduction to Maximize Information Retention in Breast Cancer Tissue Microarrays
Computational Multiplex Panel Reduction to Maximize Information Retention in Breast Cancer Tissue Microarrays Open
Recent state-of-the-art multiplex imaging techniques have expanded the depth of information that can be captured within a single tissue sample by allowing for panels with dozens of markers. Despite this increase in capacity, space on the p…
View article: A multi-encoder variational autoencoder controls multiple transformational features in single-cell image analysis
A multi-encoder variational autoencoder controls multiple transformational features in single-cell image analysis Open
Image-based cell phenotyping relies on quantitative measurements as encoded representations of cells; however, defining suitable representations that capture complex imaging features is challenged by the lack of robust methods to segment c…
View article: ME-VAE: Multi-Encoder Variational AutoEncoder for Controlling Multiple Transformational Features in Single Cell Image Analysis
ME-VAE: Multi-Encoder Variational AutoEncoder for Controlling Multiple Transformational Features in Single Cell Image Analysis Open
Image-based cell phenotyping relies on quantitative measurements as encoded representations of cells; however, defining suitable representations that capture complex imaging features is challenged by the lack of robust methods to segment c…
View article: VISTA: VIsual Semantic Tissue Analysis for pancreatic disease quantification in murine cohorts
VISTA: VIsual Semantic Tissue Analysis for pancreatic disease quantification in murine cohorts Open
Mechanistic disease progression studies using animal models require objective and quantifiable assessment of tissue pathology. Currently quantification relies heavily on staining methods which can be expensive, labor/time-intensive, incons…
View article: VISTA: Virtual ImmunoSTAining for pancreatic disease quantification in murine cohorts
VISTA: Virtual ImmunoSTAining for pancreatic disease quantification in murine cohorts Open
Mechanistic studies of pancreatic disease progression using animal models require objective and quantifiable assessment of tissue changes among animal cohorts. Disease state quantification, however, relies heavily on tissue immunostaining,…